2017 Summer Abstract of Undergraduate Research

Swanson School of Engineering Undergraduate Research Program 2017

Welcome to the 2017 Issue of the Swanson School of Engineering (SSOE) Summer Research Abstracts!

Every year, the SSOE invites undergraduates to propose a research topic of interest to study for the summer and to identify a faculty mentor willing to serve as a mentor and sponsor for their project.

Students work on innovative research with leading scientists and engineers while spending their summer at Pitt, other institutions or abroad! Four students spent their internship in Singapore at the National University of Singapore. One student traveled to Switzerland to study at the prestigious European Organization for Nuclear Research (CERN). Closer to home, students were hosted at Penn State University and University of Delaware. Within the Pitt community, several departments outside of SSOE hosted summer students: Medicine, Microbiology and Molecular Genetics, Neuroscience, Ophthalmology, Orthopedic Surgery, Pathology, Physical Medicine and Rehabilitation, Physics and Astronomy, Plastic Surgery, Psychiatry, Psychology, Rehabilitation Science and Technology, and Surgery. It was exciting to see the broad range of substantial fields that engineering students became involved in!

There are multiple programs that offer summer research opportunities to the SSOE undergraduates, the largest of these being the Summer Internship Program jointly sponsored by the Swanson School and the Provost. This year, the program funded over 60 students, with generous support from both the SSOE and the Office of the Provost. Additional support was provided by a gift from the PPG Foundation for students selected as PPG Fellows. Other support came from the Kennametal Foundation and Arconic Foundation. Further, the Swanson School study abroad program assisted students who participated in international internships.

The following individual investigators also provided support: Howard Aizenstein, William Anderst, Eric Beckman, Bryan Brown, Andrew Bunger, Markus Chmielus, Youngjae Chun, Vaughn Cooper, Richard Debski, William Federspiel, Alan George, Tae Min Hong, Alicia Koontz, Prashant Kumta, Steven Little, Ervin Sejdic, Sanjeev Shroff, Ian Sigal, Matthew Smith, Alexander Spiess, George Stetten, Patrick Thibodeau, Albert To, Rocky Tuan, Sachin Velankar, David Vorp, Guofeng Wang, Courtney SparacinoWatkins, and Savio Woo. As required of the internship, students submitted poster abstracts to a professional conference. A primary conference submission is Science 2017, hosted at the University of Pittsburgh every October.

Bioengineering students, in particular, often submit their work to the Biomedical Engineering Society (BMES); and all students were encouraged to submit their work to any professional conference(s) that their respective mentor(s) suggests.

Interns and other summer students are also invited to submit abstracts for consideration for a full manuscript in Ingenium: Undergraduate Research in the Swanson School of Engineering. Ingenium provides undergraduates with the experience of writing manuscripts and graduate students, who form the Editorial Board, with experience in peer-review and editing.

We hope you enjoy this compilation of the innovative, intellectually challenging research that our undergraduates took part in during their tenure at SSOE. In presenting this work, we want to acknowledge and thank those faculty mentors who made available their laboratories, their staff, and their personal time to assist the students and further spark their interest in research.

Larry Shuman, Senior Associate Dean for Academic Affairs David Vorp, Associate Dean for Research Mary Besterfield-Sacre, Associate Dean for Academic Affairs

Student

Student Department

Mentor(s)

Mentor Primary Department(s)

Nathan K. Fleming

Bioengineering

Aaron P. Batista

Bioengineering

Brandon Burger

Bioengineering

Bryan N. Brown

Bioengineering

Ruben M. Hartogs

Bioengineering

Bryan N. Brown

Bioengineering

Christine N. Heisler

Kathryn E. LaBelle

Eliza Schally

Bioengineering

Bioengineering

Bioengineering

Bryan N. Brown

Bryan N. Brown

X. Tracy Cui

All mentors are faculty at the University of Pittsburgh unless otherwise noted.

Title (*abstract witheld) SPATIAL MEMORY MAINTANANCE IN DORSAL PREMOTOR CORTEX LIVER DECELLULARIZATION VIA WHOLE ORGAN PERFUSION AND MECHANICAL AGITATION* EFFECT OF PNS-ECM HYDROGEL ON FUNCTIONAL RECOVERY AFTER PERIPHERAL NERVE INJURY*

Bioengineering

EFFECT OF PERIPHERAL NERVESPECIFIC EXTRACELLULAR MATRIX HYDROGEL ON FUNCTIONAL RECOVERY AFTER PERIPHERAL NERVE INJURY*

Bioengineering

EFFECT OF A PERIPHERAL NERVESPECIFIC EXTRACELLULAR MATRIX HYDROGEL ON FUNCTIONAL AND SENSORY RECOVERY FROM TRAUMATIC PERIPHERAL NERVE INJURIES*

Bioengineering

IN VITRO CHARACTERIZATION OF MELATONIN-LOADED CONDUCTING POLYMER COATINGS FOR NEURAL ELECTRODES

Shayla E. Goller

Bioengineering

Lance A. Davidson Bioengineering

Catherine A. Smith

Bioengineering

Richard E. Debski

Bioengineering

Bianca N. De

Bioengineering

William J. Federspiel

Bioengineering

COMPLEX THREE DIMENSIONAL TISSUE ASSEMBLY USING FLAT HIGHDENSITY CELL SHEETS BIOMATERIAL REPAIR OF THE RAT SUPRASPINATUS TENDON ENTHESIS DOWNREGULATION OF CXCR1 AND CXCR-2 ON HUMAN NEUTROPHILS IN EXTRACORPOREAL RECIRCULATION THROUGH HOLLOW FIBERS WITH IMMOBILIZED IL-8

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

Student

Student Department

Mentor(s)

Mentor Primary Department(s) All mentors are faculty at the University of Pittsburgh unless otherwise noted.

Grace H. Held

Chemical and Petroleum Engineering

Prashant N. Kumta Bioengineering

Fathima Shabnam

Chemical and Petroleum Engineering

Prashant N. Kumta Bioengineering

Phillip Williamson

Bioengineering

Prashant N. Kumta Bioengineering

Jeremy R. Pedersen

Bioengineering

Sanjeev G. Shroff

Bioengineering

Title (*abstract witheld) STUDY THE EFFECT OF NONPOLAR SOLVENTS AS AN ELECTROLYTE ON THE DISSOLUTION OF POLYSULFIDES IN Li-S BATTERIES ASSESSING CYTOCOMPABITILITY OF NOVEL HIGH DUCTILITY MAGNESIUM ALLOYS THE EFFECT OF ZEOLITE ADDITIVES ON ION CONDUCTIVITY OF GELPOLYMER ELECTROLYTES MECHANISMS UNDERLYING MYOFILAMENT ACETYLATIONANDPHOSPHORYLATIONMEDIATED REGULATION OF CARDIAC MUSCLE CONTRACTION* ASSESSMENT OF PATIENT HEMODYNAMICS PRE-LEFT VENTRICLE ASSIST DEVICE IMPLANT TO DETERMINE CHANCE OF RIGHT VENTRICULAR FAILURE INTERACTIONS BETWEEN WAVEFORM SHAPE AND VISUOMOTOR RESPONSE PROPERTIES IN PREFRONTAL CORTEX

Yousif J. Shwetar

Bioengineering

Marc A. Simon

Bioengineering

Jonathan A. Scott

Bioengineering

Matthew A. Smith

Bioengineering

Jacob M. Meadows

Bioengineering

George D. Stetten, University of Pittsburgh AND Hongliang Ren, National University of Singapore

Bioengineering (PITT) AND Biomedical Engineering (NUS)

PRELIMINARY DEVELOPMENT OF A LOW-COST FLEXIBLE ENDOSCOPE FOR ROBOTIC MINIMALLY INVASIVE NASOPHARYNGOSCOPY

Oliver D. Snyder

Bioengineering

George D. Stetten

Bioengineering

TEXTURE SIMULATION WITH 1DOF NORMAL TO THE SURFACE USING A LOUDSPEAKER

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

Student

Trevor M. Kickliter

Student Department

Bioengineering

Mentor(s)

David A. Vorp

Mentor Primary Department(s) All mentors are faculty at the University of Pittsburgh unless otherwise noted.

Bioengineering

Abigail M. Snyder

Bioengineering

David A. Vorp

Rachel E. Sides

Bioengineering

Justin S. Weinbaum Bioengineering

Bioengineering

Title (*abstract witheld)

COMPUTATIONAL ASSESSMENT TO CORRELATE THE EVOLUTION OF WALL STRESS WITH THE LOCATION OF DISSECTION IN THE ASCENDING THORACIC AORTA ASSESSMENT of HUMAN STEM CELL RETENTION AND HOST CELL INVASION IN AN IMPLANTED SEEDED TUBULAR SCAFFOLD STIMULATION OF ELASTIC FIBER PROTEINS BY MESENCHYMAL STEM CELLDERIVED FACTORS

Ian J. Moran

Bioengineering

Savio L-Y Woo

Bioengineering

THE DEVELOPMENT OF A Mg RING FOR THE REGENERATION OF A TORN ACL FOR HUMAN APPLICATION

Fatimah Adisa

Chemical and Petroleum Engineering

Ipsita Banerjee

Chemical and Petroleum Engineering

EXPLORING SINGLE CELLED hPSC VIABILITY USING ALGINATE HYDROGELS

Chemical and Forrest M. Salamida Petroleum Engineering

Eric J. Beckman

Chemical and Petroleum Engineering

PREDICTING PHASE BEHAVIOR OF ORGANIC SALT-WATER, TWO-PHASE SYSTEMS USING THE AIOMFAQ MODEL

Chemical and Petroleum Engineering

Manish Kumar, Penn State University

Chemical Engineering

FOULING RESISTANT MEMBRANES USING CATALYTIC CuO NANOPARTICLES

Bioengineering

Steven R. Little, University of Pittsburgh AND Honliang Ren, National Univeristy of Singapore

Chemical and Petroleum Engineering (PITT) AND Biomedical Engineering (NUS)

SEMI-AUTOMATED SEGMENTATION OF GLIOBLASTOMAS IN BRAIN MRI USING MACHINE LEARNING TECHNIQUES

Chemical and Petroleum Engineering

MICROPARTICLE TREATMENT OF PERIODONTITIS: ANALYSIS OF THE EFFECT OF SEX HORMONES ON DISEASE OUTCOMES AND CORRELATED IMMUNE RESPONSE

Nikhil Malik

Naomi Joseph

Kayla M. LeMaster

Chemical and Petroleum Engineering

Steven R. Little

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

Mentor Primary Department(s)

Student

Student Department

Mentor(s)

Kyler R. Madara

Chemical and Petroleum Engineering

Chemical and Jason E. Shoemaker Petroleum Engineering

Chemical and Nicholas P. Strauch Petroleum Engineering Chemical and Keerthi K. Gnanavel Petroleum Engineering

All mentors are faculty at the University of Pittsburgh unless otherwise noted.

Sachin S. Velankar

Chemical Engineering

Christopher E. Wilmer

Chemical and Petroleum Engineering

Title (*abstract witheld) MODELING INTERFERON RESPONSE IN PANDEMIC H1N1 INFLUENZA VIRUS INFECTED MICE USING GENE EXPRESSION DATA IMPROVING FABRICATION OF TOPOGRAPHICALLY ACTUATING VASCULAR GRAFTS SIMULATING THE NATURAL GAS FILLING RATE OF FUEL TANKS PACKED WITH METALORGANIC FRAMEWORK ADSORBANTS DEVELOPING CEMENTITIOUS MATERIALS FOR ANALOGUE EXPERIMENTS IN HYDRAULIC FRACTURING

Taylor R. DaCanal

Civil and Environmental Engineering

Andrew P. Bunger

Civil and Environmental Engineering

Qihang Ou

Civil Engineering Andrew P. Bunger

Civil and Environmental Engineering

TIME DEPENDENT HYDRAULIC FRACTURE INITIATION IN LIMESTONE AND SHALE

Christina L. Rogers

Daniel Cha, Civil Engineering University of Delaware

Civil Engineering (UD)

BIODIESEL PRODUCTION FROM WASTEWATER MICROORGANISMS: EFFECT OF BIOSOLIDS DRYING METHODS

Chlesea V. Flower

Civil Engineering Kent A. Harries

Civil and Environmental Engineering

Joseph R. Kocik

Computer Engineering

Alan D. George

Electrical and Computer Engineering

Karl W. Sewick

Electrical Engineering

Hong Koo Kim

Electrical and Computer Engineering

Henry T. Phalen

Bioengineering

Ervin Sejdic

Electrical and Computer Engineering

Evan M. Poska

Industrial Engineering

Mostafa Bedewy

Industrial Engineering

DETERMINING THROUGHCULM WALL PROPERTIES OF BAMBOO USING THE FLATRING BENDING TEST* DETERMINISTIC SPACE NETWORKING AND TIMETRIGGERED ETHERNET MODELING

LOW LOSS SURFACE PLASMON PROPAGATION AT SINGLE INTERFACE FOR ANISOTROPIC MEDIA (METAMATERIALS) DIFFERENTIAL ACTIVATION OF REST-STATE CORTICAL NETWORKS IN FIRST-EPISODE SCHIZOPHRENIA-SPECTRUM PSYCHOSIS KINETICS OF SELF-FOLDING SHAPE-MEMORY POLYMERS ACTIVATED BY LOCAL

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

Student

Student Department

Mentor(s)

Mentor Primary Department(s) All mentors are faculty at the University of Pittsburgh unless otherwise noted.

James R. Kern

Industrial Engineering

Youngjae Chun

Industrial Engineering

Seth D. Stern

Industrial Engineering

Youngjae Chun

Industrial Engineering

Danielle R. Kline

Industrial Engineering

Paul W. Leu

Industrial Engineering

Katerina A. Kimes

Materials Science Markus Chmielus

Materials Science

Pierangeli Rodríguez Materials Science Markus Chmielus De Vecchis

Materials Science

Samantha A. Schloder

Materials Science

Materials Science Markus Chmielus

Title (*abstract witheld)

BIOCOMPATIBILITY AND FUNCTIONALITY ASSESSMENT OF A NOVEL NITINOL TONGUE PROSTHETIC DEVICE TO TREAT DYSPHAGIA SUTURE GUIDE HOLDER NONINTERFERENCE TOOL INVENTION* SILICON SOLAR CELL 92.4% SOLAR SPECTRUM ABSORPTION ACHIEVED THROUGH NANOTEXTURING AND THIN FILM ETCHING BINDER JET ADDITIVE MANUFACTUTING OF MAGNETOCALORIC FOAMS FOR HIGH-EFFICIENCY COOLING BINDER JET ADDITIVE MANUFACTURING OF DENTAL MATERIAL FROM COBALTCHROME ALLOY DENSITY VARIATION IN ADDITIVELY MANUFACTURED Ti-6Al-4V

Katherine A. Brosky Materials Science Jung-Kun Lee

Materials Science

SEQUENTIAL INFILTRATION SYNTHESIS FOR HIERARCHICAL NANOSTRUCTRE COATING

Alexandra Beebout

Materials Science

MATERIALS COMPUTATION OF MAGNETIC PROPERTIES OF COBALT NANOPARTICLES

Materials Science Guofeng Wang

Sarah V. Wolfe

Materials Science Jung-Kun Lee

Materials Science

THE EFFECT OF A PEROVSKITE/TiO2 INTERFACE ON I-V CURVES, RETENTION, AND ENDURANCE PROPERTIES IN A BI-LAYER ReRAM DEVICE

Junbo Wang

Mechanical Engineering

Mechanical Engineering

THE EQUIVALENTS BETWEEN REYNOLDS NUMBER AND RAYLEIGH NUMBER I CYLINDER

Hessam Babaee

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

Mentor Primary Department(s)

Student Department

Mentor(s)

Marisa A. Wolfe

Mechanical Engineering

C. Isaac Garcia, Univeristy of Pittsburgh AND Mechanical Jerry Fuh and Lu Engineering (PITT Wen Feng National and NUS) University of Singapore

Louis K. McLinden, III

Mechanical Engineering

Student

All mentors are faculty at the University of Pittsburgh unless otherwise noted.

Title (*abstract witheld)

THE EFFECT OF PROCESS PARAMETERS ON THE TENSILE STRENGTH OF 3D PRINTED ABS AND PLA

Mechanical Engineering

AC HALL EFFECT MEASUREMENT SYSTEM FOR DEVELOPING EFFICIENT THERMOELECTRIC MATERIALS

Nitin Sharma

Mechanical Engineering

INTEGRATING FUNCTIONAL ELECTRICAL STIMULATION CONTROL AND IMU-BASED LIMB ANGLE ESTIMATION FOR DROP FOOT CORRECTION

Mechanical Engineering

PROCESS OF INSERTING OPTIMIZED LATTICE STRUCTURE FOR SELECTIVE LASER SINTERING

Sangyeop Lee

Levi S. Burner

Electrical Engineering

Shawn J. Hinnebusch

Mechanical Engineering

Albert To

Jimmy Zhang

Chemical and Petroleum Engineering

Courtney E. Medicine Sparacino-Watkins

THE PHYSIOLOGICAL ROLE OF MITOCHONDRIAL AMIDOXIME REDUCING COMPENENT 2 A HIGH-THROUGHPUT MODEL

Abraham C. Cullom Civil Engineering Vaughn S. Cooper

Microbiology and FOR BIOFILM DISPERSAL-BASED Molecular Genetics STUDIES OF EVOLUTION IN

BACTERIAL BIOFILMS*

Alyssa A. Bell

Nowa B. Bronner

Patrick H. Thibodeau

Bioengineering

Oliver M. Schulter Neuroscience

Nathaniel M. Myers Bioengineering

Eric Zhang

COMPUTATIONAL AND

Chemical and Petroleum Engineering

Bioengineering

Morgan V. Fedorchak

Ian A. Sigal

Microbiology and EXPERIMENTAL MODELING OF Molecular Genetics CYTOCHROME B5 REDUCTASE

DYNAMICS EXAMINATION OF TWO TETON CONSTRUCTS WUTH Sh95 IN THE VISUAL CORTEX

Opthalmology

THERMORESPONSIVE NIPAAmBASED GEL FOR TARGETED DELIVERY TO THE RETINA

Opthalmology

COLLAGEN FIBER ORIENTATION MAPPING WITH FOURIER PTYCHOGRAPHY POLARIZED LIGHT MICROSCOPY

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

Student

Student Department

Mentor(s)

Mentor Primary Department(s)

Shumeng Yang

Bioengineering

William J. Anderst

Orthopedic Surgery OSTEOARTHRITIS UNLOADER

Rocky Tuan

MODULATING INFLAMMATION THROUGH CARTILAGEDERIVED EXTRACELLULAR Orthopedic Surgery MATRIX FOR POTENTIAL TREATMENTS OF CARTILAGE DISEASE

Bioengineering

Rocky Tuan

EXAMINATION OF TISSUE VIABILITY AND HOMEOSTASIS Orthopedic Surgery IN AN OSTEOCHONDRAL BIOREACTOR

Bioengineering

Eric Lagasse, University of Pathology (PITT) Pittsburgh AND AND Biomedical Honliang Ren, Engineering (NUS) National Univeristy of Singapore

Madalyn R. Fritch

Kalon J. Overholt

Hannah K. Liu

Bioengineering

All mentors are faculty at the University of Pittsburgh unless otherwise noted.

THE EFFECTS OF AN

BRACE ON KNEE JOINT SPACE

Grace A. Brueggman

Bioengineering

Jennifer L. Collinger

Physical Medicine and Rehabilitation

Daniel Zheng

Computer Engineering

Tae Min Hong

Physics and Astronomy

Tyler J. Bray

Bioengineering

Alexander M. Spiess

Plastic Surgery

Shane D. McKeon

Bioengineering

Howard J. Aizenstein

Psychiatry

Katherine R. Rohde

Bioengineering

Walter Schneider

Title (*abstract witheld)

Psychology

FOUR-POINT FORTUNE-TELLERINSPIRED ORIGAMI GRASPER FOR INCREASED DEXTERITY AND LESS TISSUE DAMAGE IN MINIMALLY INVASIVE SURGERY (MIS) REACTION TIMES TO INTRACORTICAL MICROSTIMULATION IN A PERSON WITH TETRAPLEGIA ARE SIMILAR TO THOSE OF PERIPHERAL TACTILE AND VISUAL STIMULI IN ABLEBODIED SUBJECTS TRIGGER RATE MONITORING FOR THE ATLAS EXPERIMENT AT CERN DEVELOPMENT OF A 3D PRINTED, LOW COST THUMB PROSTHETIC CO-REGISTRATION OF IN-VIVO AND EX-VIVO HUMAN MRI BRAIN IMAGES CORRECTION OF GIBBS RINGING ARTIFACT IN DW-MRI WITH BIOMIMETIC BRAIN PHANTOM AS GROUND TRUTH

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

Student

Andrew N. Sivaprakasam

Shushma Gudla

Student Department

Bioengineering

Bioengineering

Mentor(s)

Alicia M. Koontz

Marina V. Kameneva

Mentor Primary Department(s) All mentors are faculty at the University of Pittsburgh unless otherwise noted.

Title (*abstract witheld)

Rehabilitation Science and Technology

INVESTIGATING WHEELCHAIR SEATING PARAMETERS AND THEIR EFFECT ON RAMP PROPULSION

Surgery

NANOMOLAR DRAG REDUCING POLYMERS (DRPs) REDUCE NEAR-WALL MARGINATION OF RIGID RBCs IN MICROCHANNELS: A POTENTIAL THERAPY FOR SICKLE CELL DISEASE (SCD)

All mentors are faculty at the University of Pittsburgh unless otherwise noted *Denotes abstract withheld to protect intellectual property

SPATIAL MEMORY MAINTANANCE IN DORSAL PREMOTOR CORTEX Nathan K Fleming, Nicholas P Pavlovsky and Aaron P Batista Sensory Motor Integration Laboratory and Engineering, Department of Bioengineering University of Pittsburgh, PA, USA Email: nkf4@pitt.edu, Web: http://www.smile.pitt.edu/ INTRODUCTION Learning a new skill begins with a high degree of variability in performance. Beginner piano players strike a disjointed chord, and an amateur bowler gutter-balls every other frame. Recent studies in neuroscience have begun to show how the brain becomes more adept at reliably driving skilled movements. A 2014 study by Wimmer et al colleagues linked variability in the neural activity during the delay period to variability in the responses during eye movement behaviors [1]. A key aspect of their ability to predict eye movement variability from neural variability was to posit that neurons act together in a cohesive network to encode the details of the upcoming movement.

Their study could only assume cohesive network activity, because each neuron was recorded individually in their study. Since we have the ability to record from dozens of neurons at once, we reasoned that we should be able to detect an even tighter relationship between neural population activity and behavior. To that end, we studied neural activity in the dorsal aspect of the premotor cortex (PMd) during reaching tasks. The goal of this project is to understand how PMd activity prior to the reach represents the details of the upcoming movement and how that representation changes throughout the movement-preparation period. We examined population neural activity recorded during a delayed memory guided reach task to test the hypothesis that PMd activity becomes representative of movement accuracy as initiation of movement nears.

METHODS A laboratory version of a demanding motor task is a “delayed reach task.” In it, a monkey must prepare, but withhold, a specific movement, until instructed to reach toward the target from memory. A delayed reach task gives us information regarding the activity of neuronal populations while memory is being accessed. This task has eight possible targets equally spaced in a circle equidistant from a center starting

point. Once the animal moves his hand to acquire the center target, one of the eight targets appears on the screen and then disappears. When it disappears, the animal must remember the location of that target while he continues holding at the center target for a variable length delay period (1000-3000 ms). At the end of the delay period, the center target disappears, signaling the animal to reach to the remembered location of the target shown earlier. After a successful reach to the target, a juice reward is received. Kinematic data is collected throughout the task using motion capture of the hand.

A 96-channel electrode array collected simultaneous neural activity. Analysis includes finding the “firing rate” (that is, action potentials per second) for each neuron during successive brief segments of the delay period, fitting each neuron’s firing rates with a “tuning curve”. Tuning curves give us an estimate of how a neuron will fire as a function of reach angle, with the peak of neural activity defining the neuron’s “preferred direction”. A population vector algorithm (PVA) brain-computer interface decoding technique is then used [2], utilizing firing rates and preferred directions, to estimate the direction of the impending reach from the firing rates of the population of neurons. We tested our hypothesis by comparing the decoded reach during each time segment to the actual reach to determine if deviations from ideal behavior were evident in the activity of the neural population.

We envisioned three possible outcomes: First, the PMd neural population might closely track the actual hand movement, as Wimmer et al. found for eye movements in the frontal eye field. Second, PMd neurons might collectively encode the location of the actual target. This would mean that the motor variability is introduced downstream from PMd, perhaps in the muscles themselves. Third, it could be that individual PMd neurons function independently, with some varying in accord with the reach movement, and others doing the opposite, or being unrelated to the movement.

To do this analysis, we divided 105 trials into those where reaches deviated clockwise, and those where reaches deviated and counterclockwise. Tuning Bias were calculated by finding the difference between preferred direction of clockwise trials versus counterclockwise trials. These values were found throughout the delay period and averaged across all neurons using a 300-millisecond binning window.

DATA PROCESSING Electrode voltage signals were band-pass filtered between 600 and 6,000 Hz to obtain raw neural activity on the electrode array. Single units were identified by spike sorting the raw waveforms offline using both window discriminators and principalcomponent analysis-based clustering (Plexon Offline Sorter, Plexon Inc., Dallas, TX).

RESULTS Initial calculations show promise in re-creating for arm movements what was published previously [1] for eye movements. However, we can ask these questions with greater resolution due to our simultaneous recordings of dozens of neurons. We analyzed 105 reach trials using 30 well-tuned neurons (as defined by the criterion of a cosine R2 fit value over 0.33). All trials were from reaches to a single target, which best decoded for direction for the final 1000 milliseconds of the delay period. Early and middle portions of the delay periods demonstrated lower correlation values than reported in the Wimmer paper (R=0.08 for early delay period and R=0.05 for middle delay period). However, in the final third of the delay period, the correlation between the PVA decode projection reach and actual reach angle (R=0.20) rose to similar values to that of the Wimmer paper (R=0.22).

A strong linear correlation exists between approaching Go Cues and a reduction in tuning bias.

Early delay period moments had strong counterclockwise biases which degrades towards zero right before a reach is made. The final binning period is the only period which strays far away from the established linear correlation.

DISCUSSION The relation of PMd activity to actual reaches during memory guided reach tasks is an important step in understanding how a network of neurons generates accurate movements. The results show a substantial improvement in movement predictability in the final 333 milliseconds of the delay period prior to the movement cue.

Our tuning bias analysis shows that late period decoding at best shows which target is being prepared for before movement is initiated. The final binning period (right before movement) had the largest deviation away from linear fit. It is postulated that this is most likely due to an anticipation of movement creating larger swing away from expected tuning bias.

These results have potential for applications in BCI prosthetics for the reduction of lag in responses to brain signaling in early portions of movements.

However, further analysis must be completed before confidence can be increased in these findings. We will continue this project by studying whether neural population attractor dynamics are present in PMd, as they were reported to be in another brain area in Wimmer et al. [1] and whether factors such as the strength of tuning of the neurons chosen for analysis can create a more accurate representation of forthcoming movements.

REFERENCES 1. Wimmer et al. Nature Neuroscience 17, 431-441, 2014.

2. Georgopoulos et al. J. Nuerosci 11, 1527-1537 ACKNOWLEDGEMENTS Appreciation goes to the Swanson School of Engineering Summer Grant board for funding this summer project and believing in the importance of this experience for undergraduate engineering students.

Figure 1: Averaged Tuning Bias across all neurons. As delay period progresses, a CCW bias of tuning curves dissipates.

IN VITRO CHARACTERIZATION OF MELATONIN-LOADED CONDUCTING POLYMER COATINGS FOR NEURAL ELECTRODES Eliza Schally, Asiyeh Golabchi, Kevin Woeppel, Ian Mitch Taylor, and X. Tracy Cui Neural Tissue Engineering Laboratory, Department of Bioengineering University of Pittsburgh, PA, USA Email: ems221@pitt.edu, Web: http://nte.bioe.pitt.edu/ INTRODUCTION Implantable neural microelectrodes provide a means of recording the activity from the nervous system and reducing the burden of neurological disease and injury in afflicted individuals. However, improving the chronic stability of these electrodes remains a major challenge due to degradation in signal quality over time caused by mechanical failure of the probe or inflammatory tissue responses. Conducting polymers such as poly (3,4-ethylenedioxythiophene) (PEDOT) and polypyrrole (PPy) can address this challenge by improving the electrochemical function and biocompatibility of neural electrodes. Further, dopants like carbon nanotubes (CNTs) bolster the conductive polymers for improved stability in chronic stimulation [1].

Conducting polymer-dopant systems have shown potential for increasing the effective surface area of the electrode and forming reliable electrically controlled drug release systems [2, 3]. Melatonin has been shown to have anti-inflammatory effects in the nervous system by many mechanisms including inhibiting the caspase-1 cell death pathway and scavenging reactive oxygen species. Here, we examine the melatonin loading and release capabilities of PEDOT/CNT and PPy/SfNP electrode coatings in vitro. Achieving successful drug release in vitro provides a foundation for future in vivo experiments.

METHODS All electrochemical procedures were performed on a Gamry Potentiostat using Gamry Framework software with a three-electrode setup, using either glassy carbon electrodes (GCEs) or insulated stainless steel wire working electrodes, Ag/AgCl reference electrode, and a platinum counter electrode. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were conducted on bare and coated electrodes in phosphate buffered saline (PBS), with CV ranging

from -0.6 to 0.8 V and EIS ranging from 1 to 100,000 Hz. Drug release stimulations were conducted in PBS by subjecting the working electrode to -1 V for 5 s immediately followed by 0 V for 5 s for 10 cycles.

The stimulating solution was analyzed and replaced with fresh PBS after each 10-cycle round.

For the PEDOT/CNT coating, CNTs were functionalized with negatively charged carboxylic acid upon treatment with nitric and sulfuric acid.

Then, 1 mg mL-1 CNTs were sonicated in a 1.5 mg mL-1 melatonin solution with 0.02 M EDOT monomer to facilitate loading of melatonin into the inner cavities of the CNTs. The solution was polymerized via chronocoulometry at 0.9 V onto GCEs until a charge density of 50 mC cm-2 was reached.

For the PPy/SfNP coating, thiol nanoparticles were synthesized by sol-gel process from tetraethyl orthosilicate and (3-mercaptapropyl) trimethoxysilane. Ellman’s Reagent confirmed the presence of thiol groups on the surface of the nanoparticles. The resulting thiol nanoparticles were isolated via centrifugation and reacted with hydrogen peroxide (30%) and sulfuric acid (‌%) to oxidize the thiol to sulfate. The sulfate nanoparticles were brought to a pH between 8 and 9 with 1N sodium hydroxide. SfNPs isolated from 2ml of the solution prepared above were added to 1ml of 0.5M PPy solution. The solution was polymerized at 0.9 V via chronocoulometry onto insulated stainless steel wire until a total charge of 1 mC was reached. The nanoparticles incorporated into the PPy film were dissolved with hydrofluoric acid to create a porous film. Model drug fluorescein was loaded into the porous film by holding the coated wires at a potential of 0.4 V in a 0.01 M solution of fluorescein until the current decreased to a plateau. A layer of PPy/Fluorescein was then polymerized (in solution of 0.5 M Py and 0.1 M fluorescein, at 0.9 V via

chronocoulometry until a total charge of 0.1 mC was reached) to cap the porous PPy film.

All drug release data was gathered with spectrophotometry. A standard curve was created for fluorescein in PBS with an excitation wavelength of 485 nm and an emission wavelength of 525 nm. The drug release of the PPy/dissolved SfNP coating was compared to a control stainless steel wire electrode coated only with a 0.1 mC PPy/fluorescein cap.

RESULTS The CV plots of the PEDOT/CNT coated electrodes showed an oxidation peak for melatonin around 700 mV. This peak is a reliable method for assessing melatonin concentration, however, the oxidation of melatonin resulted in the irreversible formation of a fouling product that stuck to the electrode surface.

The fouling product’s redox peaks are at about -0.1 V. This was confirmed by the fact that the fouling product’s oxidation peaks became larger while the melatonin oxidation peaks became smaller as the cyclic voltammetry progressed through three cycles, as shown in Figure 1.

The PPy/SfNP coating was successful in that the

Figure 1. CV plot of a PEDOT/CNT coated GCE after being soaked in a melatonin solution to demonstrate the oxidation peaks of melatonin and its fouling products.

SfNPs were an adequate dopant. When examined with scanning electron microscopy as in Figure 2, it was obvious that the nanoparticles were homogeneously distributed within the PPy film.

Figure 2. SEM image of a PPy/SfNP coated stainless steel wire electrode.

Further, the quantity of drug released from the PPy/dissolved SfNP film in the first round of stimulation was 0.01 μg, which was double that of the control (0.005 μg).

DISCUSSION It is extremely notable that the SfNPs discussed herein can act as adequate dopants for an electrically polymerized conducting polymer as they are cheaply synthesized, unlike CNTs. The need to overcome the irreversible oxidation of melatonin at about 700 mV points future work toward the PPy/SfNP coating, since the drug doesn’t need to be subjected to more than 400 mV to be loaded. Thus, the improved drug release capabilities of the PPy/SfNP coating may be clinically relevant. Future work would also have to confirm the bioactivity of the released melatonin in order to provide an effective therapy.

REFERENCES 1. Luo et al. Biomaterials 32, 5551-5557.

2. Luo et al. Biomaterials 32, 6316-6323, 2011.

3. Wadhwa et al. J Controlled Release 110, 531-541.

2006 ACKNOWLEDGEMENTS This research was funded by NIH R01NS089688.

Eliza Schally was supported by the Swanson School of Engineering, University of Pittsburgh.

COMPLEX THREE DIMENSIONAL TISSUE ASSEMBLY USING FLAT HIGH-DENSITY CELL SHEETS Shayla Goller1, Uma Balakrishnan1, Lance Davidson1,2,3 Departments of Bioengineering, 2Developmental Biology, and 3Computational & Systems Biology, University of Pittsburgh, Pittsburgh, PA 15213 USA Email: seg89@pitt.edu Blue™ (5 mg/mL) dextrans to trace cell lineage.

INTRODUCTION Dorsal tissue was explanted from gastrula stage Tissue engineering aims to create functional human embryos (stage 12.5) in Danilchik’s for Amy (DFA) tissues in a laboratory setting. The African clawed solution. These tissues were dissociated in frog, Xenopus laevis serves as a robust source of Ca2+/Mg2+-free DFA and the superficial epithelial primary embryonic cells, as its cells are easier to layer was discarded. Cells from 10 native tissues culture and manipulate than human cells. Easier cell were centrifuged (4000g for 10 minutes) in a culture and manipulation make it a suitable model custom-made chamber on a smooth agarose organism for the development of techniques that substrate. can later be moved to human cell culture.

The resulting cell sheets were removed and Approaches to in vitro tissue fabrication combine combined to create adjacently fused tissues, and various cells, induction factors, and methods to layered tissues. To fabricate adjacent fused tissues, establish tissue geometry. The traditional method cell sheets were adjacently co-cultured under glass used to establish complex tissue geometry employs and encouraged to fuse using inert plastic shim. The a scaffold, but seeding scaffolds often results in a fused tissue was immediately fixed in relatively low cell density, which interferes with paraformaldehyde (PFA) containing 0.25% alignment, assembly, and interaction between cells glutaraldehyde overnight. Layered tissues were [1]. Scaffold-free methods allow tissues to selfcreated by centrifuging cell sheets on top of each assemble and thereby circumvent many of the other in a single chamber at 4000g for 10 minutes. problems associated with scaffold use; however, These tissues were fixed immediately and after 3 methods such as bioprinting and microextrusion hours of culture in DFA with 0.1% antibiotic. Once subject cells to high strain and can lead to lower cell fixed, samples were then washed in phosphateviability [2,3].We have developed a scaffold-free buffered solution (PBS) and then incubated method that uses centrifugation instead of overnight in the fibronectin antibody 4H2 (1:500). bioprinting to fabricate cell sheets of high cell Following a second wash in PBS, samples were density and viability from the primary embryonic incubated in secondary antibody (anti-mouse FITC, cells of X. laevis. Maintaining centrifugation 1:250) overnight. Tissues were dehydrated in parameters at 4000g for 10 minutes allows for isopropanol, clear using Murray’s Clear (2:1 benzyl creation of thin laminar sheets of approximately benzoate: benzyl alcohol). Cleared cell sheets were 5,000 cells and 158±19.8 μm thick, which maintain imaged on the confocal microscope. Images were the cell density of native tissues, and remain viable adjusted and analyzed using ImageJ to determine for over 24 hours. Here, we explore methods of the extent of tissue fusion between cell sheets of combining these cell sheets to create complex different origin [5]. tissues. Sequential centrifugation and co-culturing methods allow us to combine individual tissues into larger, highly dense structures useful for future RESULTS Fusion of two aggregates was defined as two tissue engineering applications. separate cell populations adhering to one another and acting as one tissue. Tissue mixing occurred if METHODS cells from one origin within the fused tissue X. laevis embryos were obtained, fertilized, and demigrated into the population cells from another jellied according to established protocols [4]. origin, instead of remaining as two distinct Embryos were injected before the 4-cell stage with populations on either side of the tissue. Aggregates 8nl of trimethylrhodamine (2.5 mg/mL) or Cascade 1

fuse after either adjacent culture or sequential centrifugation, indicating that both methods were effective in the creation of one tissue. Minor mixing of marked cells was observed in sequential centrifugation when fixing occurred after a 3hr culture in DFA and antibiotic, indicating cell travel within the tissue. This mixing takes some time, as it was not observed when fixed immediately after sequential centrifugation or after adjacent culturing.

The unification of multiple flat aggregates in a controlled way indicates that small, dense, cell aggregates can be arranged into tissues with specific shape.

complex tissues can enable the development of future tissue science and engineering projects.

Future work may involve expanding the size of these cell sheets, varying cell types, and further investigation into the mechanical properties of these aggregates. Distinctly patterned tissues may be expanded upon by incorporating more than one cell type to mimic more sophisticated function and communication.

Sheets containing simple combinations of one cell type will be useful in determining how exactly these methods will relate to large tissues that are less conveniently centrifuged and stitched together.

REFERENCES [1] Athanasiou, Kyriacos A., et al. " Ann. Rev. Biomed. Eng 15 (2013): 115-136.

[2] Norotte, Cyrille, et al. Biomaterials 30.30 (2009): 5910-5917.

[3] Smith, Cynthia M., et al. Tissue Eng. 10.9-10 (2004): 1566-1576.

[4] Sive, Hazel L., et al. CSHL Press, 2000.

[5] Schneider, C. A., Rasband, W. S. and Eliceiri, K. W. Nat Methods (2012). 9, 671-675.

Figure 1. (a) Tissue is microsurgically isolated from a stage 12.5 frog embryo, dissociated, and its cells are centrifuged to make a laminar sheet of cells. (b) Photo of an aggregate. (c) Two aggregates are cocultured to create one tissue. (d) Confocal image of cocultured aggregates. (e) One aggregate centrifuged on top of another to create a tissue. (f) Confocal image of centrifuged tissue fixed immediately after centrifugation. (f’) Confocal image of centrifuged tissue fixed after three hours of culture.

DISCUSSION Both sequential centrifugation and co-culture can be used to effectively combine dense, flat, cell sheets into laminar, complex tissues. Access to such

ACKNOWLEDGEMENTS This work was supported in part by the SSOE and grants to L.A.D. from the NIH (R01 HD044750 and R56 HL134195) and the NSF (CMMI-1100515).

U.L.B. was supported by the Beckman Scholars Program at the University of Pittsburgh. Disclaimer: Any opinions, findings and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the NIH or NSF.

BIOMATERIAL REPAIR OF THE RAT SUPRASPINATUS TENDON ENTHESIS Catherine A. Smith, Gerald A. Ferrer, João Novaretti, Benjamin B. Rothrauff, Rocky Tuan, Volker Musahl, Richard E. Debski Orthopaedic Robotics Laboratory, Department of Bioengineering University of Pittsburgh, PA, USA Email: cas309@pitt.edu Web: http://www.engineering.pitt.edu/labs/ORL/ INTRODUCTION: Rotator cuff injuries are a highly prevalent and significant clinical problem in the general population. Though surgical repair of small tears has been shown to be clinically successful, there is up to a 94% re-tear rate with larger tears [1].

High re-tear rates may be a result of the poor innate healing capacity of the rotator cuff enthesis [2], Current methods of augmenting healing at the enthesis include allografts, extracellular matrix (ECM), platelet rich plasma (PRP), growth factors and stem cells [3]. Several biomaterials have been investigated to assess the structural properties in healing rat rotator cuffs with promising results, including bone marrow derived stem cells (MSCs) transduced with scleraxis, and fibroblast growth factor (FGF-2) [4,5]. However, the ideal biomaterial or combination of biomaterials to augment healing of rotator cuff repair surgery is unknown. The objective of this study was to assess the effects of different biomaterials (fibrin, GelMA, ADSCs and TGFβ) alone and in combination on the tensile properties of healing rat rotator cuff tendons.

METHODS: One hundred and twenty-nine fresh-frozen rat humeri were evaluated following a full-thickness transection of the supraspinatus and infraspinatus tendons after 4 weeks of healing. The 8 treatment groups for the rotator cuff injuries included: no repair, repair only, fibrin, GelMA, fibrin + adipose derived stem cells (ADSCs), GelMA + ADSCs, fibrin + ADSCs + TGFβ, and GelMA + ADSCs + TGFβ. The eight groups were further divided into two sub-groups of 1) Acute: tears created and immediately repaired with 4 weeks of healing and 2) Chronic: tendons were injected with botulinum toxin to induce fatty degeneration, tear created, 8 weeks of caged activity, repair, and 4 weeks of healing [6].

Each specimen was thawed at room temperature and the humeral head was cerclaged to prevent humeral head avulsion. Supraspinatus tendons were kept hydrated with physiologic saline solution, gripped using custom clamps and mounted in a materials testing machine (Instron, Model 5965, Norwood, MA, USA) equipped with a 50N load cell. The experimental protocol consisted of a 0.2N preload, preconditioning between 0.2-1N for 10 cycles, and a load-tofailure test. All tests were performed at an elongation rate of 5mm/min. The structural properties (ultimate load, ultimate elongation, stiffness and energy absorption to failure) were determined from the load-elongation curve.

DATA PROCESSING: A chi-square test was performed to evaluate the effect of the biomaterials on the failure mode. A two-tailed independent t-test was performed to compare chronic and acute tear groups (combining all treatment groups together) on each structural property. A one-way ANOVA with a post-hoc Bonferroni test was performed to assess the effect of the different treatment groups on each structural property. Significance was set at p < 0.05.

RESULTS: The most common failure modes among all groups were either at the enthesis or midsubstance. Treatments involving GelMA failed at the enthesis at a higher frequency than treatments involving fibrin (p < 0.05). Treatment groups that utilized GelMA had a failure rate at the enthesis of 43.2% while groups using fibrin failed at the enthesis only 23.4% of the time. No intact controls failed at the enthesis. When combining all treatment groups together, chronic

tears had significantly lower ultimate load (26%) and energy absorption to failure (36%) compared to acute tears (p < 0.05). No difference between treatment groups was found for ultimate load, ultimate elongation, stiffness or energy absorption to failure (p > 0.05). However, intact controls were found to have a significantly greater ultimate load and stiffness than all treatment groups. Ultimate load for intact controls were 248% greater than the treatment groups for chronic tears (Figure 1). Similarly, stiffness for intact controls were 597% greater than the treatment groups for chronic tears (Figure 2). No difference was found between the treatment groups and intact controls for ultimate elongation and energy absorption to failure.

studies, the chronic tears were weaker than acute tears in terms of having a lower ultimate load, supporting the validity of the rat model used [6,7]. The results show no statistical difference between the treatment groups for all structural properties, indicative that the biomaterials used are able to restore the site of injury to a similar degree. Differences between this study and others may be attributed to the specimen preparation, test setup, healing time and injury model used. For example, surgical repair of a two-tendon cuff tear in a rat and subjective delineation of the healing supraspinatus and infraspinatus tendon may introduce variability in the results of structural properties of the healing complex. Despite variability in the results, previous studies that used a chronic massive cuff tear rat model and investigated the structural properties of the healing rotator cuff also found large variability and had similar findings [6,7].

Therefore, to improve upon the current study, future studies will investigate the mechanical properties of the tendons to better assess the quality of the healing tissue. Since the current animal model may be too small to detect differences for a chronic massive cuff tear, future work will also use a larger animal model (e.g. sheep) to increase the likelihood of detecting differences between treatments.

REFERENCES: 1. Galatz et al. JBJS, 2004.

2. Angeline & Rodeo. Clin Sports Med, 2012.

3. Montgomery et al. Curr Rev Musc Med., 2011.

4. Gulotta et al. AJSM, 2011.

5. Ide et al. JSES, 2009.

6. Killian et al. AJSM, 2015.

7. Killian et al. JOR, 2014.

DISCUSSION: The finding that GelMA causes the tendons to fail at the enthesis most often indicates that some biomaterials might better strengthen the enthesis than others, ie, fibrin may strengthen the enthesis better than GelMA. Consistent with previous

ACKNOWLEDGEMENTS: Support from the University of Pittsburgh Swanson School of Engineering, Department of Bioengineering, Department of Orthopaedic Surgery, and NSF Fellowship Grant No. 1247842 is gratefully acknowledged.

DOWNREGULATION OF CXCR-1 AND CXCR-2 ON HUMAN NEUTROPHILS IN EXTRACORPOREAL RECIRCULATION THROUGH HOLLOW FIBERS WITH IMMOBILIZED IL-8 Bianca N. De, Alexander D. Malkin, William J. Federspeil. John A. Kellum, and Kai Singbartl Medical Devices Laboratory, McGowan Institute of Regenerative Medicine University of Pittsburgh, PA, USA Email: bid6@pitt.edu, Web: www.mcgowan.pitt.edu/medicaldevices INTRODUCTION Sepsis occurs when the bodyâ&#x20AC;&#x2122;s systemic inflammatory response to infection damages its own tissues and organs. In the USA, it is estimated that sepsis affects over 1,000,000 hospitalized patients per year [1]. The mortality rate for sepsis is high, but there is no specific FDA approved treatment [2].

The current standard of care is treatment of the underlying infection and cardiorespiratory organ support through intravenous fluids, vasopressors, mechanical ventilation, and oxygen therapy.

These therapies fail to address the underlying pathophysiology of sepsis. During an inflammatory response, macrophages at the infected site produce the cytokine interleukin-8 (IL-8). Neutrophil Gprotein-coupled receptors CXCR-1 and CXCR-2 bind IL-8, inducing chemotaxis down the IL-8 gradient. When IL-8 spills out into the bloodstream, neutrophils migrate into healthy tissues. Neutrophils produce proteolytic factors and reactive oxygen species that are intended to damage pathogens, but also affect healthy tissue, causing organ failure. At high IL-8 concentrations, neutrophils down-regulate expression of CXCR-1 and CXCR-2, decreasing the chemotactic response to IL-8[3]. An extracorporeal circuit device that passes blood through hollow fibers with immobilized IL-8 on the inner lumen surface without increasing serum IL-8 may inhibit neutrophil migration, preventing sepsis-related organ damage.

The goal of this study is to test a scaled-down extracorporeal recirculation setup with an immobilized IL-8 fiber module in series with an adsorbent scavenging module for targeted

neutrophil CXCR-1/2 down-regulation without IL-8 leaching into circulation.

METHODS Two-module test and control recirculations were set up with peristaltic pumps for 1mL/minute flow.

The majority of the 10mL total volume was contained in a reservoir to simulate patient blood volume. Fiber modules contained 25 dialyzer fibers each (Baxter/Gambro Inc., Deerfield, Illinois, USA). The first module in the loop contained fibers with ligands covalently attached to amine anchors on the lumen surface. The test module contained immobilized IL-8 and the control module contained immobilized human albumin. The fibers in the second module adsorbed any proteins that leached from the first module.

5% Bovine serum albumin (BSA) solution was recirculated through the test recirculation with immobilized IL-8 module for 60 minutes. The leached IL-8 concentration in the reservoir at the end of recirculation was tested using the Invitrogen Human IL-8 Ultrasensitive ELISA Kit (Carlsbad, CA, USA). Reservoir samples taken at 30 and 60 minute time points were incubated with equal volumes of human whole blood obtained with University of Pittsburgh IRB approval.

Human whole blood was also recirculated through the device for 60 minutes, and then incubated for 105 minutes. A baseline negative control and a free IL-8 spiked positive control were also incubated.

Samples were taken immediately after recirculation and after the incubation period.

All whole blood samples were lysed and immunostained with Anti-human CXCR-1 and CXCR-2. Flow cytometry was used to measure receptor expression and determine if downregulation occurred.

RESULTS After one hour of recirculation, the 5% BSA contained 32pg/mL IL-8. Neutrophils incubated with the recirculated BSA samples maintained CXCR-1/2 expression above 90% of baseline for all time points.

In neutrophils recirculated with the control hAlb module, CXCR-1/2 expression did not change from baseline. In neutrophils recirculated with the IL-8 module, CXCR-1 expression decreased to 58% of baseline and CXCR-2 expression decreased to 56% after one hour. Expression of CXCR-1 and CXCR-2 recovered to 116% and 112% of baseline respectively at 165 minutes. The IL-8 spiked positive control maintained CXCR-1 and CXCR-2 expression under 50% and 20% of baseline respectively at both time points.

DISCUSSION The immobilized IL-8 module caused downregulation of CXCR-1/2 expression in neutrophils immediately after whole-blood recirculation, but receptor expression recovery occurred within hours.

It is possible that free IL-8 in solution or more exposure to immobilized IL-8 can cause longer down-regulation.

The whole blood samples that were incubated with recirculated BSA buffer did not demonstrate decreased CXCR-1/2 down-regulation. This indicates that free IL-8 leached into solution was not a significant contributing factor in the decreased in receptor expression that was achieved during whole-blood recirculation. Instead, all downregulation occurred within the fiber modules.

The extremely low concentration (32 pg/ml) of IL-8 in the BSA solution after 1 hour of recirculation confirms that the reduced CXCR-1/2 expression in whole-blood recirculation was not caused by free IL-8. This low concentration also confirms that the scavenging module successfully adsorbed any IL-8 that leached from the IL-8 immobilized fibers before it could reach the reservoir.

In future studies, investigation of the functional impact of CXCR-1/2 downregulation and the ideal receptor expression recovery time period will influence the recirculation setup.

REFERENCES [1] Martin GS. Sepsis, severe sepsis and septic shock: changes in incidence, pathogens and outcomes. Expert Rev Anti Infect Ther.

2012;10(6):701-6.

[2] Levinson AT, Casserly BP, Levy MM. Reducing mortality in severe sepsis and septic shock.

Semin Respir Crit Care Med. 2011;32(2):195-205.

[3] Rose JJ, Foley JF, Murphy PM, Venkatesan S. On the mechanism and significance of ligandinduced internalization of human neutrophil chemokine receptors CXCR1 and CXCR2. J Biol Chem. 2004;279(23):24372-86.

ACKNOWLEDGEMENTS This research was funded jointly by the Swanson School of Engineering and the University of Pittsburgh Office of the Provost. Research was conducted at the McGowan Institute of Regenerative Medicine. Aminated dialyzer fibers were provided by Baxter Inc.

Study the effect of non – polar solvents as an electrolyte on the dissolution of polysulfides in Li-S batteries Grace H. Held Next Generation Energy Conversion and Storage Technologies Laboratory, Department of Chemical Engineering University of Pittsburgh, PA, USA Email: grh30@pitt.edu 1. INTRODUCTION Demand for long-lasting, high-energy density, and cost-effective rechargeable electrical energy storage devices (EES) has increased due to increased power requirements of mobile devices, laptops, and electric vehicle/plug-in electric vehicles (EV/PEV). Li-ion battery (LIB) technology, the most popular technology for rechargeable EES has reached its limits and highercapacity alternatives such as lithium-sulfur batteries (LSBs) are of increasing interest.

Sulfur has an industrial production cost of 4 $ kg−1 and a theoretical energy density of 2600 W h kg-1 compared to LIBs price of 100 $ kg−1 and an energy density of 350 W h kg-1 [1, 2]. The significant decrease in cost and increase in energy density makes LSB technology an attractive alternative to LIB technology.

While theoretically LSBs are superior to LIBs, there are issues with the reduction of elemental sulfur within the battery resulting insoluble polysulfides (PS). The dissolution and diffusion of the PS into the electrolyte cause the loss of active material and capacity fade within Li-S cells continuing to hinder the much awaited commercialization path.

[1]. PS are polar and are dissolved by polar solvents commonly used in the cells (DOL: DME, 50:50 vol%). One way to minimize PS dissolution in the electrolyte is by introducing nonpolar solvents to the electrolytes to minimize the dissolution and diffusion of the PS resulting in improvements in the Li-S battery cyclability. These studies were planned in the present study, the results of which are described and discussed.

2. MATERIALS AND METHODS The study used ten different nonpolar solvents (listed in order of increasing polarity): cyclohexane (CYCLO), toluene (TOL), tetrahydrofuran (THF), 1,2dimethoxyethane (DME), n-methyl-2pyrrolidone (NMP), 1,3-dioxolane (DOL), sulfolane (SULF), dimethyl sulfoxide (DMSO), acetonitrile (ACN), and tetraethylene glycol dimethyl ether (TETRA) [3]. All solvents were acquired from Sigma Aldrich (anhydrous, 99.8% purity) and used as received. The electrolytes were prepared by adding 1.8 M LiCF 3 SO 3 (99% purity) and 0.6 M LiNO 3 (99.99% purity) to each solvent and mixing for 45 minutes. The ten solvents were then mixed in 50:50 (vol%) to yield forty-five unique combinations (Table 1) which were tested in Li-Li symmetric cells and the corresponding ionic conductivities were measured.

For ionic conductivity measurements, 2025-type coin cells were assembled in an argon filled glove box with Li metal act as both working and counter electrodes, Celgard 2500 polypropylene as separators and the various prepared electrolytes. Impedance analysis for ionic conductivity measurement of electrolytes was performed between 100,000 Hz to 0.001 Hz at 10 mV using a Gamry series G Potentiostat (Gamry Instruments, Inc., Warminster, PA). The ionic conductivity of the electrolytes was calculated using the solution resistance (Rs) measured from the impedance plots and taking the thickness and surface area of the cell into account.

The electrolytes that showed ionic conductivities close to commercial Li-S battery electrolyte (DOL: DME, 50:50 vol%) were considered successful for this research and were tested in Li-S cells. The cathodes for the cells were prepared by slurry coating a 60:30:10wt% (sulfur: super-P): poly (vinyldene fluoride)) dispersion in NMP (Nmethyl pyrrolidone) onto aluminum foil. The electrochemical cycling of the Li-S cells were performed in Arbin BT200 battery testing system at a charge/discharge rate of 100mAh/g.

3. RESULTS AND DISCUSSION The impedance analysis on singlesolvent electrolytes showed that THF, DOL, DME, TETRA, and NMP had high roomtemperature ionic conductivities (Figure 1 and Table 1) suggesting their potential as cosolvents along with non-polar solvents.

Figure 1: Nyquist plot of the five best conducting single solvent electrolytes.

The impedance analysis on the forty-five electrolyte combinations produced by mixing the ten single solvents in 50:50 vol% revealed that twenty-six co-solvent electrolytes had ionic conductivities close to commercial LiS battery electrolyte (Table 1).

Electrolytes that showed poor ionic conductivities when tested individually (ie: DMSO, SULF, CYCLO, and TOL), showed improvement in ionic conductivities when mixed with other solvents independent of their polarity (i.e.: 1:1 (vol:vol). DMSOTOL, DMSO-ACN, and CYCLO-SULF (Table 1)). Combinations of polar-nonpolar solvents such as CYCLO-DOL, CYCLONMP, TOL-THF, TOL-DME, TOL-TETRA, and TOL-NMP showed promising values of ionic conductivities to be used as a suitable electrolyte for Li-S battery.

4. CONCLUSIONS Study on the effect of introducing non-polar solvents as electrolytes for Li-S batteries revealed several promising cosolvent candidates with excellent ionic conductivities. These electrolytes could potentially prevent PS dissolution in Li-S batteries. Detailed study of the chemical and electrochemical properties of these novel discovered electrolyte candidates are underway.

REFERENCES [1] S. Zhang, K. Ueno, K. Dokko, M. Watanabe, Advanced Energy Materials, 5 (2015) 1500117-n/a.

[2] M. Hagen, S. DĂśrfler, P. Fanz, T. Berger, R. Speck, J. TĂźbke, H. Althues, M.J. Hoffmann, C. Scherr, S. Kaskel, Journal of Power Sources, 224 (2013) 260-268.

[3] A.D. McNaught, A.D. McNaught, Compendium of chemical terminology, Blackwell Science Oxford, 1997.

ACKNOWLEDGEMENTS Support of Department of Energy, Edward R. Weidlein Chair funds and PPG Foundation are acknowledged.

Table 1.Conductivity of single and co-solvent electrolytes.

Solvents DMSO CYCLO TOL THF SULF

Cond (mS/cm) 1.770037 2.76E-06 0.000333 6.024677 1.234056

Solvents DOL DME TETRA NMP ACN

Cond (mS/cm) 5.078823 10.52401 3.810046 14.42752 0.082541

Solvents DMSO-TOL CYCLO-SULF CYCLO-DOL CYCLO-NMP TOL-THF

Cond (mS/cm) 6.28267 0.622262 0.265123 1.34617 0.09202

Solvents TOL-DME TOL-NMP TOL-TETRA DOL-DME TETRA-NMP

Cond (mS/cm) 2.924387 9.259259 2.790428 9.726113 3.981906

ASSESSING CYTOCOMPABITILITY OF NOVEL HIGH DUCTILITY MAGNESIUM ALLOYS Fathima Shabnam, Jingyao Wu, Abhijit Roy, Prashant N. Kumta Department of Bioengineering University of Pittsburgh, PA, USA Email: fas32@pitt.edu INTRODUCTION Magnesium-based alloys have attracted researchers for decades due to its ability to degrade in vivo, biocompatibility and suitable mechanical properties.

Extensive application possibilities have been explored, such as orthopedic implant, sutures and vascular stents. These new devices have the potential to reduce the number of second surgeries as well as long-term adverse effects due to perennial existence of the device. During the degradation procedure, magnesium alloys do not produce any toxic corrosion product; however, its rapid, uncontrolled degradation rates pose a concern, as the surrounding tissues get affected [1,2]. Currently there is no study conducted to evaluate the cytotoxicity of magnesium-based alloys on airway epithelium cells. The aim of the study is to assess in vitro cytotoxicity of our proprietary ultra-high ductility (UHD) magnesium alloys specifically for tracheal stent application.

In this study, MTT test and DAPI & F-action staining was performed to determine the effects of degradation products of these magnesium alloys with different ratios on the human bronchial epithelial cell line (BEAS-2B). These results demonstrated comparable cytotoxicity of our proprietary magnesium alloys to commercial pure magnesium and AZ31 alloys.

METHODS BEAS-2B cells cell culture The bronchial epithelial cells (BEAS-2B cell line) were cultured in Bronchial Epithelial Cell Growth Medium (BEGM). The flasks were pre-coated with a mixture of fibronectin, bovine collagen type I, bovine serum albumin (BSA) in culture medium.

Cells were cultured in BEGM medium in the cell culture incubator.

MTT Assay The MTT assay is used to assess the cell metabolic activity and the cytotoxicity of the extracts. Surface areas of three samples from each group were calculated. The samples were polished using SiC abrasive paper of 1200 grit, cleaned ultrasonically

in acetone solution, and placed in a closed hood with ultraviolet light for 30 min on each side. The samples were then immersed in BEBM with a surface area-to-extraction ratio of 1.25 cm2/mL for 72 hrs. The extract was then added at 10%, 25%, 50%, and 75% concentrations to the seeded 8000cells/well in a 96-well plate for 1 and 3 days respectively. The negative control was pure medium with no extract, and the positive control was 10% DMSO culture medium. The cytotoxicity of the extract was then tested using the Vybrant MTT Cell Proliferation Assay Kit. Phenol red free media and MTT were added, and the plate was left to incubate for 4 hrs. After adding SDS solution, the plate was left to incubate for 16 hrs before reading at 570nm absorbance using a plate reader.

To evaluate the ion concentration, 100Âľl of each extract was added to 9.9mL of distilled water. Two standards were used to calibrate. ICP-OES (Inductive Coupled Plasma Optical Emission Spectroscopy) quantifies the presence of small amounts of metal ion concentrations.

DAPI & F-Actin Staining DAPI & F-Actin staining stains the nucleus and the cytoskeleton of the cell, making the morphological changes visible. The extract from the cell culture plates were fixed with 4% paraformaldehyde (PFA) for 10 min. Triton X was added before washing with PBS. Phalloidin and DAPI were added for staining. Images were taken with florescence.

STATISTICAL ANALYSIS For the MTT tests, the average and standard deviation of the three samples for each group was taken.

RESULTS Figure 1(a) shows the increase in magnesium and lithium ions concentrations after immersing the alloys in culture medium for 72 hrs. As seen in Figure 1, there is a steep rise in both ion concentrations, with AZ31 alloy having the highest magnesium ion concentration. Except Mg ions, our proprietary alloy also release high amount of Li.

(a)

Control Mg AZ31 Alloy 1 Alloy 2 Alloy 3

Ion concentration (ppm)

2000 1800 1600 1400 1200 1000 800 600

75% extract 25% extract 240

50% extract 10% extract

75% extract 25% extract 240

(b)

220

220

200

200

180

180

Cell viability (%)

2200

Cell viability (%)

2400

160 140 120 100 80

(c)

160 140 120 100 80

60

60

40

40

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20

20

0

0

400

50% extract 10% extract

0

Figure 1 (a) Magnesium and Lithium ion concentrations in the alloy extract. MTT test of the BEAS-2B cells in different ratio of alloy extract (b) day 1; (c) day 3.

Mg

Li

Mg

AZ31

The MTT test shows the cell viability of the BEAS2B cells after 1 day and 3 days. Alloys 1, 2 and 3 appear to show less viability than pure Mg, and AZ31 on day 1. On day 3, the cell viability improves and appear similar among all the groups.

Figure 2 compares the morphology of the BEAS-2B cells between day 1 and day 3. On day 1 and day 3, the cells in the different groups look similar, indicating that the alloys did not have an affect on the morphology. In the control group on day 3, the cells appear to have aggregated.

Alloy 1

Alloy 2

Alloy 3

Mg

AZ31

Alloy 1

Alloy 2

Alloy 3

the impact is not as concerning and likely to have no significant affect.

From the results of the DAPI & F-Actin staining, it can be seen that the alloys did not have a negative impact on the morphology. One reasoning behind the aggregation seen in the control group compared to the other groups could be that the presence of magnesium ions prevents aggregation of the cells (Figure 1(a)). The nucleus becoming more visible on day 3 for alloy 1 may indicate that the cells were locked in the synthesis phase (which can be seen in the cell cycle study not shown here).

The in vitro experiments conducted indicated the effects of the magnesium alloys on the BEAS-2B cells that could be visualized under the microscope.

This, combined with the in vivo experimentation that is currently proceeding, will elucidate the biocompactability of each alloy. The results of this study will help determine the suitability of the alloys for tracheal stent application.

Figure 2. Images of the BEAS-2B cells day 1 and day 3 of DAPI & F-Actin staining. (scale bar = 50µm).

DISCUSSION The trends seen in the ICP-OES results are crucial in understanding the results of other experiments.

This is because the effect of the alloys on the cells is primarily due to its composition, and determining the ion concentration explains the exact affect.

Based on the ICP-OES data and the MTT results, it can be proposed that the lithium ion concentration impacted the cell viability. However since the levels had risen close to pure magnesium control on day 3,

REFERENCES [1] Myrissa, Anastasia, et al. “In vitro and in vivo comparison of binary Mg alloys and pure Mg.” Materials Science and Engineering: C, vol. 61, 2016, pp. 865–874 [2] Chou, Da-Tren, et al. “In vitro and in vivo corrosion, cytocompatibility and mechanical properties of biodegradable Mg–Y–Ca–Zr alloys as implant materials”. Science Direct. 2013.

ACKNOWLEDGEMENTS This research was funded jointly by Dr. Kumta via the Edward R. Weidlein Chair Professorship funds, the Swanson School of Engineering, and the Office of the Provost. I would like to especially thank Dr. Kumta, Dr. Roy, Mr. Wu, and my family.

The Effect of Zeolite Additives on Ion Conductivity of Gel-Polymer Electrolytes Philip A. Williamson, Pavithra M. Shanthi, Ramalinga Kuruba, Prashanth J. Hanumantha and Prashant N. Kumta Center for Energy University of Pittsburgh, PA, USA Email: phw17@pitt.edu Introduction The increasing demand for powerful electrochemical energy storage devices (EESDs) has spurred the research into novel EESD technologies and chemistries for use in a variety of applications. Among these exploratory technologies are lithium-sulfur batteries incorporating a metallic lithium anode and a sulfur cathode in the form of a composite material.

Manthiram et al. note that sulfur is an attractive cathode material as it has a theoretical charge capacity of 1672 mAh/g, which is an order of magnitude higher than those of conventional transition metal-oxide cathodes. This high capacity is based on the reversible reaction of sulfur with lithium to form lithium sulfide (Li2S) by accepting two electrons per sulfur atom, compared to the one or fewer electrons accepted per transition-metal ion in the insertion-oxide cathodes of conventional batteries. This reaction takes place over a series of intermediary reactions wherein lithium reacts with cyclic sulfur to form polysulfides (Li2Sx, 2 < x <=6).

Unfortunately, these polysulfides present a technical challenge to the performance of the cell as they are soluble in common electrolytes and can shuttle between the electrodes of the cell, passivating them. One proposed solution to prevent polysulfide shuttling is the generation of gel-polymer electrolytes (GPEs). Rao et al. make the claim that polysulfides are less soluble in GPEs and this leads to a suppressed shuttling effect.

Their data, along with data from Mamorstein et al., shows that Li-S batteries utilizing a gel-polymer electrolyte experience a slower capacity fade, an effect attributed to suppressed polysulfide shuttling.

Researchers have also investigated how incorporating additives and fillers into gel-polymer electrolytes affect their performance. One such group of additives are zeolites. Nunes-Pereira et al. assert that zeolite additives improve the ion conductivity of GPEs due to their crystal structure providing sites for ion transport. In our

research, we are also interested in exploring the possibility of using zeolite fillers in GPEs to suppress polysulfide shuttling. In our present work, we perform initial characterization of polymer mattes incorporating the zeolite ZSM-5 as filler to test the claim that zeolites improve ion conduction and to investigate their performance as gel-polymer separators.

Procedure Solutions of 10wt% polymer and 1wt% ZSM-5 in DMF were prepared. Pure PVdF-HFP and PAN were used as the polymer in two solutions and the third solution used a blend of 50wt% PVdF-HFP and 50wt% PAN. Three more solutions identical to these were prepared as a control without ZSM-5. All solutions were stirred at 40°C for 2 hours. Electrospun mattes were then prepared from these solutions by electrospinning 10mL of each solution onto a rotating drum at room temperature.

After electrospinning was completed, each matte was allowed to dry in vacuum for 12 hours to evaporate any remaining DMF. The electrospun mattes were then punched into 1.75cm diameter circular separators. The separators were then placed in an argon glovebox where temperature was maintained at 25°C and O2 and H2O levels were maintained below 5ppm. Separators were then allowed to soak for 10 minutes in an electrolyte composed of 1.8M lithium triflate (LiCF3SO3) and 0.1M lithium nitrate (LiNO3) in a 50:50 by volume dioxolane/dimethoxyethane (DOL/DME) solvent. After soaking, coin cells were assembled by sandwiching each GPE between two layers of metallic lithium in 2025-type coin cells.

The morphology of the electrospun mattes was studied with scanning electron microscopy using a JEOL JSM6510 machine. Electrochemical impedance spectroscopy was performed on the Li/GPE/Li coin cells using a Gamry Potentiostat applying an AC voltage of 10 mVRMS with frequency ranging from 100 kHz to 10 mHz. Equivalent circuit modeling was performed

using Z-view 2.0 (Scribner Associates Inc.) to obtain the bulk resistance value for each GPE. Analysis & Discussion a) PVdF-HFP w/ ZSM-5 Figure 1 shows images from our three electrospun mattes incorporating ZSM-5. We see that the PVdF-HFP fibers with zeolite are much thinner compared to b) PAN w/ ZSM-5 the other mattes.

There are also spherical particles present. These may be unmixed ZSM-5 or they may be globules produced during the c) PVdF-HFP/PAN (50:50) w/ ZSM-5 elctrospinning Figure 1: SEM images taken of a) process. The images PVdF-HFP with ZSM-5, b) PAN of PAN with zeolite with ZSM-5, c) PVdF-HFP/PAN and of the 50:50 (50:50) with ZSM-5.

PVdF-HFP/PAN blend with additives show thicker fibers with some bulges and fewer independent particles.

Nyquist plots obtained from the EIS of our GPE coin cells are shown in Figure 2. These data were used to determine the ionic conductivity of each GPE, taking separator thickness and area into account. These values are shown in Table 1. As can be seen from the values in Table 1, there is minimal difference between the separators made from pure polymer versus those with zeolite added.

Conclusions To produce a proper composite of polymer with zeolite, we aim to see which polymers mix most homogenously with ZSM-5. PAN seems to fit this description best based on our SEM images. While thinner fibers such as PVdF-HFP may offer more surface area for ZSM-5 to deposit, we see large spherical structures in the PVdFHFP matte. These may be unmixed ZSM-5, but they may also be globules produced by the electrospinning process. A more homogenous structure, as seen in Figure 1a, will offer better structural stability and may be more effective at suppressing polysulfide shuttling.

Figure 2: EIS Nyquist plots for the GPE systems.

Table 1 GPE Composition PVdF-HFP PVdF-HFP w/ ZSM-5 PAN PAN w/ ZSM-5 PVdF-HFP/PAN (50:50) PVdF-HFP/PAN (50:50) w/ ZSM-5 Liquid Electrolyte

Ionic Conductivity (S cm-1) 1.351E-03 3.153E-03 3.654E-03 2.997E-03 2.091E-03 2.839E-03 4.283E-03

In regard to ion conductivity, our data did not show a significant difference between GPEs with zeolite and those without. This may be because the amount of zeolite we used in our electrospun mattes (10 wt%), was too low. This conclusion warrants further studies on the effect zeolite proportion has in GPE ion conductivity.

Forthcoming Investigation Further research needs to be conducted investigating the effects of zeolite on GPE ion conductivity. Additionally, our group will investigate how Li-S cells with zeolite infused GPEs perform after many cycles in a chargedischarge test. FTIR and XRD analysis of these GPEs with zeolite, before and after cycling, is also needed to better understand the chemical effects zeolites have on gel-polymer electrolytes.

References 1. Manthiram et al. Chem. Rev. 114, 11751−11787, 2014 2. Rao et al. Journal of Power Sources 212, 179185, 2012 3. Mamorstein et al. J of Pow. Sources 89 , 219– 226, 2000 4. Nunes-Pereira et al. J of Electroanalytical Chem. 689, 223–232, 2013 Acknowledgements Support for this research was provided by the Swanson School of Engineering, Department of Energy, Edward R. Weidlein Chair funds and the Office of the Provost.

ASSESSMENT OF PATIENT HEMODYNAMICS PRE-LEFT VENTRICLE ASSIST DEVICE IMPLANT TO DETERMINE CHANCE OF RIGHT VENTRICULAR FAILURE Yousif Shwetar, Timothy Bachman, and Marc A. Simon Department of Bioengineering, Swanson School of Engineering University of Pittsburgh, Pittsburgh PA 1521 Email: yjs4@pitt.edu

INTRODUCTION The Left Ventricular Assist Device (LVAD) has been a life changing technology allowing patients suffering from end-stage heart failure to carry out normal everyday activities. However, LVADs only support the left side of the heart, leaving the right side without any assistance [4]. Right Ventricle failure is an adverse event experienced by 20% of patients who receive an LVAD [3]. RV failure continues to be a widespread problem post LVAD implantation. Right sided Heart failure occurs when the right ventricle loses its pumping function possibly causing congestion. Although patients can be assisted with inotropic support, 10% - 15% of patients still require a Right Ventricular Assistance Device (RVAD) implantation. Inotropes are medications that affect myocardial contractility by either increasing or decreasing contractility.

Implantation of RVAD post LVAD implantation can increase one’s morbidity and mortality rate from 21% to 44% [2].

Potential predictors of RV failure include high central venous pressure (CVP), a high CVP/pulmonary capillary wedge pressure (PCWP) ratio, decreased cardiac index, low right-ventricular stroke work or high pulse volume recordings. These values are acquired via Right Heart Catheterization (RHC). However, no single factor has been consistently found in all studies [2]. We are attempting to determine who is at risk of RV failure prior to surgery so that they can either receive adequate medical support or receive a right ventricular assist device simultaneously.

HYPOTHESIS We are testing the hypothesis that there is a difference between dP/dt or compliance in patients that are suffering from severe right ventricular heart failure post left ventricular assist device implantation.

METHODS

The study consisted of 32 patients all of which had left sided systolic class D heart failure as defined by the ACC and the AHA [1]. Pressure Waveforms were received from standard right heart catheterization which was performed by a trained cardiologist. Cardiologist inserted a Swan Ganz catheter via the jugular which is fed through the Superior Vena Cava, Right Atrium, Right Ventricle, and the Pulmonary Artery. PAC insertion using a Swan Ganz Catheter is done to obtain conventional properties of hemodynamic waveforms. In addition to standard measurements, maximal rate of pressure change with respect to time (dP/dt) and Compliance which is defined as stroke volume over pulse pressure can also be acquired.

DATA ACQUISITION Once the Catheter is in place, a screenshot is captured by the WITT catheter system (Philips®).

This screenshot is put through a custom MATLAB code (MathWorks® Natick MA, United States).

The screenshot undergoes a digitization process where the waveform is traced in the code to create a MATLAB generated waveform. This new traced waveform is then put through another part of the code that creates a mean representative beat. This part of the code takes the MATLAB generated waveform and separates each beat, allowing the user to exclude beats that either have too much noise or other physiologic problems. It is also important that selected beats are in sync with one another, avoiding the possibility of creating a beat that has non-existent characteristics. Analysis of the mean representative beat gives hemodynamic parameters such as Systolic, diastolic, and mean pressures, as well as ± dP/dt STATISTICAL ANALYSIS Using Excel, a statistical analysis of the patients was done calculating the mean and standard deviation of + dP/dt and compliance. These values were used to create graphs whilst comparing other factors such as amount of time on inotropic support.

This study included two major groups, one group being 0-14 days on inotropic support, and the other being anything greater than 14 days. Patients with 14 days or greater of inotropic intake are considered to have RVF. RESULTS Thirty-two patients were enrolled (25 male, mean age 54±13, age range 23-73). Five patients were classified as RVF after LVAD. Mean time from CL study to implant was 10±11 vs 7±7 days for those with vs without RVF, respectively. There was no

significant difference between patients with and without RVF for all hemodynamic parameters recorded, although right atrial pressure trended to be higher in RVF (17 ± 8 vs 11 ± 5 mm Hg, P=0.13).

Figure 1: Bar graph representation of dP/dt data (Left, P=0.92) and compliance data (Right, P=0.73). Red represents patients with RVF while blue represents patients without RVF.

DISCUSSION Both patients with Heart Failure and patients without Heart Failure shown in Figure 1 show no significant differences in their compliance values.

However, Figure 1 shows patients with a lower dP/dt are generally more prone to Heart Failure.

Despite these findings, the large variability of both dP/dt and compliance for patients without heart failure are too large to derive any meaning from these results. Although data in table 1 shows a correlation between lower hemodynamic values and Heart Failure, literature has proven that these are not meaningful.

LIMITATIONS Data acquisition of +dP/dt was sometimes not possible due to noise that occurred during PAC insertion (n=5, none with RVF). This can occur due to arrhythmias, dampening of the pressure signal due to air or blood in the catheter or pressure transducer, or catheter whip causing artificially elevated systolic and reduced diastolic recordings.

In some cases, this precluded measuring +dP/dt within early systole. Therefore, +dP/dt was not an obtainable value for 6 patients that did not have RVF. This study shows that dP/dt and compliance can be calculated for LVAD patients with and without RVF. However, signal variability limited ability to detect differences. Future studies should include a larger subject pool, and use of micromonometers instead of a Swan Ganz catheter to provide a higher fidelity signal particularly during early systole REFERENCES 1.

American Heart Association. (May 8, 2017). Classes of Heart Failure. http://www.heart.org/HEARTORG/Conditions/HeartFailure/ 2.

Patlolla, Bhagat a, “Right-ventricular failure following left ventricle assist device implantation.” Current Opinion in Cardiology. 28(2):223-233, March 2013 3.

“TandemHeart for Right Ventricular failure”, Outreach for clinical Guidance on improving LVAD Outcomes. 2013;30;07.

4.

“VAD Training”, thoratec, http://www.thoratec.com/videos/mp-mcs.aspx#mp_hmII_sic

ACKNOWLEDGEMENTS Swanson School of Engineering and the Office of Provost gave me the funding to conduct this summer research. Patient data was acquired from UPMC Presbyterian Hospital.

Table 1: Average and standard deviation of standard Hemodynamic measurements

Patient Category: Patients without Heart Failure Patients with Heart Failure All Patients

SBP 55.4±12.3 49.1±6.60 54.1±11.6

DBP 28.0±6.36 23.4±10.6 27.1±7.38

MAP 39.0±7.54 34.2±7.74 38.1±7.67

Pulse Pressure 27.3±9.86 25.6±7.21 27.0±9.28

INTERACTIONS BETWEEN WAVEFORM SHAPE AND VISUOMOTOR RESPONSE PROPERTIES IN PREFRONTAL CORTEX Jonathan A. Scott, Sanjeev B. Khanna, Matthew A. Smith Visual Neuroscience Laboratory, Department of Bioengineering University of Pittsburgh, PA, USA Email: jas492@pitt.edu, Web: http://smithlab.net/ INTRODUCTION Cortical brain computer interfaces (BCI) have proven to be a valuable research tool for investigating the brain, and additionally a potential solution for patients with some form of paralysis.

BCIs rely upon the population of neurons being recorded. Therefore, understanding how these neurons interact and are connected could improve the ability of BCIs. How putative inhibitory (narrow spike width) and excitatory (broad spike width neurons communicate, particularly in prefrontal cortex (PFC), has not been closely examined. PFC has been implicated in many different cognitive functions, including eye movement generation, learning, attention, and working memory. We were interested in how excitatory and inhibitory subpopulations communicate during the sensorimotor transformation from processing a visual stimulus to making an eye movement. PFC is an ideal candidate for studying interactions between inhibitory and excitatory neurons during this transformation, due to its wide variety of response properties and its role in eye movement generation.

Of particular interest is the connection between spike (inhibitory/excitatory) and response (visual/motor) properties in neuronal populations in PFC, As well as the interactions between different subpopulations.

METHODS This study consisted of two adult, male rhesus macaque monkeys (Macaca mulatta) implanted with 100-electrode Utah arrays in PFC. We implanted in the right hemisphere for Monkey P and the left hemisphere for Monkey W. A titanium headpost was attached to the skulls of both monkeys to immobilize the head during experiments.

Subjects were trained to perform a memory-guided saccade task. For the task, the subjects maintained fixation on a yellow dot at the center of a flat-screen CRT monitor positioned 36 cm from their eyes for

200 ms. After the fixation period, a peripheral target cue was presented at one of forty conditions. A condition is one of five distances from the center of the screen (5, 7.5, 10, 12, 14.5) and at one of eight angles (0o, 45o, 90o, 135o, 180o, 225o, 270o, and 315o). The target cue had duration of 50 ms. The subjects made their saccade to the location of the target cue when the fixation point turned off 500 ms after the target cue turned off.

Across all trials, 1186 neurons were recorded from both subjects. 824 neurons were recorded from Monkey P over the course of 13 days and 362 neurons were recorded from Monkey W over the course of 8 days.

DATA PROCESSING AND ANALYSIS Spikes from the electrode recordings were identified by threshold crossings, sorted offline with an automated algorithm, and further refined manually.

We used a waveform classifier previously used by our lab to determine the probability of a given neuron being either inhibitory or excitatory [1].

The spike counts were then found by extracting all the spikes within a window for baseline, visual, and motor epochs. Baseline spike count was all the spikes that occurred before the target cue turned on.

Visual spike count was all the spikes that fired 50 ms to 150 ms after the target cue turned on. The motor spike count was all the spikes that fired 50 ms before the saccade onset to 50 ms after the saccade onset. The spike counts were used to calculate the firing rate for each category. The firing rates were used to calculate a d’ sensitivity index, which was used to determine if a neuron was visual, motor, or visuomotor. Neurons with a mean d’ above 0.15 were considered visual neurons, neurons with a mean d’ value below -0.15 were considered motor. Neurons with a d’ value between -0.15 and 0.15 were considered visuomotor.

To determine the functional connectivity between pairs of neurons in inhibitory/excitatory subpopulations, we measured spike count correlation (r sc ), which measures the tendency for responses of pairs of neurons to co-vary to a stimulus. Spike count correlation is calculated as the Pearson correlation coefficient between the spike counts of two neurons. Pairs of were grouped into three subpopulations: inhibitory/inhibitory pairs, inhibitory/excitatory pairs, and excitatory/excitatory pairs.

RESULTS Using our waveform classifier, we were reliably able to separate narrow (inhibitory) and broad (excitatory) waveforms. Figure 1 below shows the different waveform shapes for inhibitory and excitatory neurons.

Figure 1. Waveforms of all neurons classified as either narrow spiking (inhibitory, red) or broad spiking (excitatory, green).

Once the neurons were separated into visual, motor, and visuomotor, we were able to compare the spike widths for each category of neurons. Figure 2 shows the cumulative distribution for each category. Motor neurons tended to have a narrower spike width, suggesting this subpopulation might include more inhibitory neurons than the visual or visuomotor subpopulations.

We were unable to find a significant different in r sc pairs for the different subpopulations. Figure 3 shows a histogram of the normalized density of r sc for the three subpopulations.

Figure 3. r sc densities for inhibitory/inhibitory (red), excitatory/inhibitory (green), and excitatory/excitatory (blue) pairs.

DISCUSSION Using our waveform classifier, we were able to reliably separate out putative inhibitory and excitatory subpopulations. When examining these subpopulations as a function of their visual-motor response, we found that motor neurons were more likely to be inhibitory, which agrees with previous literature. However, we found that visuomotor neurons were more likely to be excitatory while previous literature found that visuomotor neurons were more likely to be inhibitory [2].

Our other findings (r sc ) suggest a more nuanced approach is necessary to determine how response properties differences vary in excitatory/inhibitory subpopulations. Other response properties that could be examined are firing rate when the animal is asleep or the relationship between neuron firing rate and the local field potential.

REFERENCES 1. Snyder et al. J. Neurophysiol 116, 1807-1820, 2016.

2. Cohen et al. J. Neurophysiol 101, 912-916, 2009.

ACKNOWLEDGEMENTS Funding was provided by the Swanson School of Engineering.

Figure 2. Cumulative distribution of spike width for motor (orange), visuomotor (black), and visual (blue) neurons.

PRELIMINARY DEVELOPMENT OF A LOW-COST FLEXIBLE ENDOSCOPE FOR ROBOTIC MINIMALLY INVASIVE NASOPHARYNGOSCOPY Jacob M. Meadows, Bok Seng Yeow, and Hongliang Ren Laboratory of Medical Mechatronics, Department of Biomedical Engineering National University of Singapore, Singapore Email: jmm367@pitt.edu, Web: http://bioeng.nus.edu.sg/mm/ INTRODUCTION Minimally invasive surgery (MIS) has become increasingly common because of the improved patient safety and comfort that comes from using smaller incisions and more advanced technology in the operating room. Smaller incisions put the patient at lower risk of blood loss and infection as well as decrease recovery time. Therefore, it is of significant clinical interest that minimally invasive techniques be explored for all types of surgical procedures.

In diagnosing nasopharyngeal carcinoma (NPC), a head and neck cancer arising in the nasopharynx most common in East Asia and Africa, minimally invasive techniques may be employed via a transnasal approach to surveil the nasopharynx with increased safety and patient comfort [1]. Because NPCs are most common in regions with typically lower access to expensive healthcare resources, it is important to develop a lower cost and rapidlyproducible tool for robotic nasopharyngoscopy to diagnose NPCs [2].

The developed preliminary device employs simple bending and actuation methods that allow for lowcost manufacturing as well as customizability for specific clinical circumstances. The device was characterized in terms of its bending ability and through a mock operation test via a rapidlyprototyped phantom model.

MATERIALS AND METHODS SolidWorks 2016 (Dassault Systems, Waltham MA) was used to design, model, and simulate various early-stage ideas, as well as the model the final design for 3D printing.

For manufacturing of the camera housing, tendon anchoring region, and attachment piece, an XYZ Nobel 1.0A SL 3D printer (XYZprinting Inc., New Taipei City Taiwan) was used to print with UV curable resin photopolymer (~40-50% acrylic monomer, ~35-50% urethane acrylate, ~5% photoinitator) material. For manufacturing of the bending region and early-stage prototypes, an Objet260 Connex360 PolyJet 3D printer (Stratasys, Eden Prairie MN) was used to print with a combination of VeroClear and TangoBlack (FLX9070) material.

In addition, 0.2mm Nylon fishing wire, a 6mm outer diameter, a 4mm inner diameter polyethylene tube, and 1.25mm outer diameter polyimide tubes were used in the final assembly. Further, a Micromot drill (Proxxon, Hickory NC) was used to make minor adjustments to 3D printed parts.

A micro ScoutCam™ 3.45 (Medigus, Omer Isreal) was used as the endoscope camera to obtain photos and videos in this device. The specifications for this camera include a stainless-steel camera housing of 3.45mm diameter and 12mm length, 160,000 effective pixels, 400px x 400px resolution, 140° field of view, 5mm – 100mm depth of field, and HDMI video output. An external monitor and light source were also used for video and photo collection from the endoscope.

RESULTS In the bending region, there are simple square cuts in each side of the tube, which allows for bending in two directions. Upon pulling of a cable, the cuts in the bending region give flexibility and allow curvature in the direction pulled. The maximum bending angle of the device is 90°, which is sufficient for NPC surveillance and transnasal maneuverability. The problem of tangling cables

was solved by weaving cables through bending cuts, ensuring proper bending upon pulling.

Figure 1: 3D-printed and assembled prototype of preliminary design. Entire device has an outer diameter of 6mm and a length of 30cm. The preliminary model is composed of camera housing and cable anchoring region, bending region, and cable conducting region. In panel A device is at rest, in panel B device is fully bent, and in panel C is a top view of the endoscope. Squares in background are 1cm by 1cm.

Low-cost manufacturing was also employed in a different thin plastic tube model; the same bending and flexibility was achieved with a thin plastic tube using the same simple cuts. Both models performed well in a mock NPC surgery test, demonstrating large viewing angles and significant maneuverability.

Images from this test can be seen in Figure 2. The primary benefits of this design are lower cost and enhanced customizability. Variations in the shape and spacing of bending region cuts allowed for customizing flexibility and workspace.

DISCUSSION In terms of the design process and development, initial ideas were first modeled in SolidWorks and tested for feasibility with SolidWorks simulation.

These initial simulations were analyzed for proper bending and to assess the possibility of deformation in the bending region. Basic square cuts in each side of the tube were sufficient to allow bending in both directions with small amounts of force. Also, a simpler design minimized the risk of deformation or other damage to the bending region [3]. Therefore, more advanced bending mechanisms beyond this were not explored for this preliminary design.

The primary benefits of this design are (1) low cost and (2) enhanced customizability.

The fully functional camera with endoscope camera incorporated was produced by 3D printing, but it was demonstrated that the same bending and flexibility at the same diameter could be achieved with simply a straw using the same cuts.

CONCLUSIONS The primary objective of this project was to develop a functioning, low-cost, and customizable endoscope model for minimally invasive nasopharyngoscopy.

This objective was achieved, but future studies should be done to expand upon this project. Future directions include building a model with a smaller, 1.2mm endoscope camera for increased patient comfort, more accurate phantom tests of the device, further characterization of device workspace, incorporation of a light source into the device, and mathematical description of device bending and tendon movement.

REFERENCES 1. Yu H, IEEE Robotics and Automation Letters (2016) Jan 2016. Vol. 1(2), pp. 1172-1178.

2. Hao SP, Chang Gung Med J. (2010) JulAug;33(4):361-9.

3. Yu H, Wu L, Wu K, Lim CM and Ren H (2016) IEEE Robotics and Automation Letters., Jan, 2016.

Vol. 1(2), pp. 1172-1178.

Figure 2: Photos of endoscope camera video feed from phantom NPC surgery test, including entry (A), front view (B), leftmost view (C), and rightmost view (D). Ruler attached for scale (centimeters)

ACKNOWLEDGEMENTS I would also like the acknowledge the University of Pittsburgh Swanson School of Engineering, Office of the Provost, and Study Abroad Office for providing funding, and the National University of Singapore for administrative support.

Texture Simulation with 1-DOF Normal to the Surface using a Loudspeaker Oliver Snyder, Dr. George Stetten, Dr. Roberta Klatzky VIALab, Department of Bioengineering University of Pittsburgh, PA, USAEmail: ods7@pitt.edu, Web: http://vialab.sp.ri.cmu.edu/ INTRODUCTION Many modern commercial technologies have, as one of their primary goals, to provide an immersive and engaging experience for the user, via smart phones, video games, personal computers, etc.

Towards this end, monitors and loudspeakers have seen significant improvements in quality and/or price. However, haptic (the sense of touch) technology has lagged far behind audio and video.

To advance haptic research and technology and enhance consumer immersion, the authors are developing an affordable Texture Simulation Device (TSD) to simulate 2D texture of a surface, by actuating with a single degree of freedom (DOF) normal to the surface, in response to motion tangential to that surface. The TSD will potentially have uses in virtual reality applications such as textiles marketing, as well as in basic psychophysics research. The goal of this project is to explore two primary questions: (1) Can a textured surface be simulated with only 1 DOF? (2) Will 1 DOF provide the right kind of sensation to fool the human operator? The TSD has evolved from a previous speaker-based haptic device that simulates tissue forces for surgery [Khera 2016].

METHODS With the goal of creating an affordable and reasonably high-quality simulation of surface textures, a 5â&#x20AC;? loudspeaker forms the primary 1-DOF actuator and a Raspberry Pi 3 (RPi) is used as the controller (Fig. 1). Three sensors provide input to the simulation. To sense position, a choice between a computer trackpad and a linear soft potentiometer (LSP) is provided. The trackpad returns 2D position and the LSP returns 1D position and force applied by the user. To access the LSP, the trackpad is physically removed from its mounting slot. Latency issues with the trackpadâ&#x20AC;&#x2122;s USB communication have led the authors to focus initially on the LSP, which produces a simple analog voltage. The third

sensor is an IR proximity sensor, mounted beneath the speaker to provide the vertical displacement of the speaker cone. Voltage signals from the LSP and optical sensor are read by the RPi through a 12-bit ADC (ADS1015). The output signal is sent from the RPi through a 12-bit DAC (MCP4822) to a power linear amplifier H-Bridge circuit, which drives the loudspeaker. The ADC and DAC communicate via I2C and SPI respectively. A 3D printed scaffold was created in SolidWorks and glued to the cone of the speaker to provide a sturdy platform for the trackpad and LSP. The texture generation programming was implemented in C, while experimental procedures and graphical user interfaces were created with the PsychoPy Python toolkit.

Fig. 1. Texture Simulation Device prototype.

RESULTS AND DISCUSSION Initial, informal testing revealed a multitude of unforeseen challenges in the device. The first is that the user must be isolated from confounding sensations such as the native texture of the LSP, surface friction, and audible noise. The noise problem has been solved with noise cancelling headphones, and the friction and native texture problem with a small strip of tape wrapped over the

skin in contact with the TSD. Another challenge arises from trying to use an active surface to simulate what is normally passive. When the user actively explores the device’s surface, a “riding” sensation rather than a texture may be felt. To convince the user that they are sensing a textured surface, the device must indistinguishably mimic a passive surface.

Despite the difficulties encountered, there have been many indications that the device is successful. When a user explores the device with a sufficiently isolated sense of touch, they report feeling a texture.

In-house testing of several standard waveforms have yielded some interesting results. When a sawtooth wave is created on the surface, users can distinguish the direction of the wave crests and report that going against the peaks of the wave feels easier. This result is very significant because it demonstrates the quality and resolution of the generated textures, as well as the TSD’s ability to create textural features that are detectable by humans.

When testing user discrimination of three basic waveforms, sinusoid, square, and sawtooth, it was determined that all three can be percieved as distinct textures. For example, the sawtooth wave has been reported to feel like a zipper.

Tests involving variation of parameters such as waveform, spatial frequency, and amplitude have provided the most meaningful information. It has been found that only amplitudes within a certain range produce a texture. When amplitude strays out of the texture range on either end, the sensation becomes that of just vibration. It has also been determined that higher spatial frequency waveforms require less amplitude to induce a texture feeling.

Similar to amplitude, only frequencies within a specific range feel like a texture. When the frequency is set too high, the waveform loses discriminability due to the limited resolution of the DAC and ADC. It is believed that this effect is due

to spatial aliasing of the presented waveform. When the frequency is set too low, the sensation of texture is replaced with the aforementioned riding sensation.

CONCLUSIONS We have made significant progress in developing a new, inexpensive device for rendering textures. A number of basic challenges have been identified and addressed. The authors have plans to characterize the psychophysical properties of the textures generated by the TSD through more extensive research involving volunteer subjects.

ACKNOWLEDGEMENTS Funded by the Swanson School of Engineering REU program and NSF grant IIS-1518630.

REFERENCES [Khera 2016] Khera, A.; Lee, R.; Marcovici, A.; Yu, Z.; Klatzky, R.; Siegel, M.; Shroff, S.G.; Stetten, G. One-Dimensional Haptic Rendering Using Audio Speaker with Displacement Determined by Inductance. Machines 2016, 4, 9.

COMPUTATIONAL ASSESSMENT TO CORRELATE THE EVOLUTION OF WALL STRESS WITH THE LOCATION OF DISSECTION IN THE ASCENDING THORACIC AORTA Trevor M. Kickliter, Kory J. Blose, Justin S. Weinbaum, Thomas G. Gleason and David A. Vorp Vascular Bioengineering Laboratory, Department of Bioengineering University of Pittsburgh, PA, USA Email: tmk77@pitt.edu, Web: http://www.engineering.pitt.edu/vorplab/ INTRODUCTION Acute dissection of the ascending thoracic aorta (ATA) is a devastating phenomenon with a mortality rate as high as 80% if left untreated [1]. To avoid this outcome, medical protocol recommends surgical intervention once the aortic diameter exceeds 5.5 cm.

However, dissection can occur at diameters above or below this guideline. In fact, Pape et al. found that nearly 60% of 591 patients studied exhibited type A aortic dissection at diameters <5.5 cm [2]. Moreover, aortic surgery carries an 8% risk of stroke and a 2.5% risk of death. Hence, clinicians must determine when surgical risks are outweighed by the risk of dissection [3]. This necessitates both a more accurate predictor of dissection and a greater knowledge of the evolution of ATA biomechanics.

Dissection occurs when hemodynamic stresses exceed bonding forces between wall lamina. As such, peak wall stress (PWS) may be a better marker for this clinical event than diameter measurements.

As wall stress is directly proportional to the local radius of curvature, local curvature can be used to identify regions of high wall stress. However, aortic geometry can change without detectable differences in stress, therefore these two markers must be assessed separately. Consequently, the primary goals of this study were to examine changes in aortic wall stress with time and to assess the correlation of PWS and curvature with the location of dissection.

METHODS CT scans were collected from dissected (n=15) and non-dissected (n=5) patients at 1 to 4 time points via Dr. Gleasonâ&#x20AC;&#x2122;s clinical practice at UPMC. On average, 2.8 scans were collected per patient with an average of 0.97 years between scans. These scans were segmented into virtual 3D models via pixel thresholding in Mimics. Models were refined in Geomagic and exported to Abaqus 6.13, where they were meshed into quadrilateral shell (S4R) elements.

The branch arteries were fixed in all degrees of

freedom, and an evenly-distributed pressure of 120 mmHg was applied to the inside of the wall. The wall was assigned a uniform thickness of 2.3 mm, and the stress-strain response of the wall was modeled using a strain energy function (W) of the following form: đ?&#x153;&#x152;đ?&#x153;&#x152;0 đ?&#x2018;&#x160;đ?&#x2018;&#x160; =

đ?&#x2018;?đ?&#x2018;?

2 2 [expďż˝đ??´đ??´1 đ??¸đ??¸đ?&#x153;&#x192;đ?&#x153;&#x192;đ?&#x153;&#x192;đ?&#x153;&#x192; + đ??´đ??´2 đ??¸đ??¸đ??żđ??żđ??żđ??ż + 2đ??´đ??´3 đ??¸đ??¸đ?&#x153;&#x192;đ?&#x153;&#x192;đ?&#x153;&#x192;đ?&#x153;&#x192; đ??¸đ??¸đ??żđ??żđ??żđ??ż ďż˝ â&#x2C6;&#x2019; 1] 2

Here, c, A 1 , A 2 and A 3 are material parameters and E θθ and E LL are components of the Green Strain. The above equation assumes the ATA wall to be hyperelastic, non-linear, incompressible and anisotropic. [4]. The parameters for the above equation are displayed in Table 1.

Table 1: Material parameters [4] Aneurysmal Non-Aneurysmal 0.043 0.053 c (MPa) 8.9 2.8 A1 8.4 3.1 A2 4.9 3.8 A3 Models were assigned material orientations in MATLAB (MathWorks, Natick, MA). Finite element analysis was performed in Abaqus/Standard, which mapped the von Mises stress at each element, as shown in Figure 1.

Figure 1: Sample finite element analysis output.

The elements on the finite element mesh best representing the site of dissection were selected by a vascular surgeon blinded to the stress values.

DATA PROCESSING Post-processing was conducted in MATLAB, during which nodal values of von Mises stress, Gaussian, and mean curvatures were recorded. From these data, the mean wall stress (MWS) and location and magnitude of PWS were calculated. To compare stresses between time points, stresses at corresponding locations at consecutive time points were paired and fit to a 1:1 trendline in which stresses at the earlier and later time points represented the x and y axes, respectively. The correlation between the two sets of results was assessed using an R2 value that depicts the goodness of fit of the trendline.

Nodes at which the stress exceeded 90% of the PWS were identified and grouped according to proximity in 3D space. The percentage of nodes in each concentration and the average Gaussian and mean curvatures within the site of dissection were reported.

RESULTS PWS was equivalent in patients that went on to dissect and in non-dissected patients (2 sample T test: p=0.731). The PWS was located above the left coronary artery on the lesser curvature for 70% of scans. Notably, in no case did the location of PWS match the dissection site identified by the surgeon.

Both the PWS and MWS changed negligibly between time points for both material models. The average Gaussian and mean curvatures at the site of dissection were not found to be significantly different from the average curvatures for the whole model (paired T test: p=0.546 and p=0.218 for the Gaussian and mean curvatures, respectively). The R2 values for a 1:1 relation between stresses at consecutive time points are shown in Figure 2.

The R2 value was less than 0.7 for 83% of comparisons, indicating a poor conformity to a 1:1 relation and suggesting a general difference in stresses at corresponding locations between time points. On average, the mean percent difference in von Mises stress at corresponding locations between time points was 17%Âą2%.

DISCUSSION In this work, we have shown an effective technique to quantify the evolution of the aortic stress field. Our findings agree with previous studies suggesting that the biomechanics of the ATA evolve over time [5].

Additionally, because wall stress is primarily a shape-driven phenomenon, it is intuitive that the stress field changes along with aortic morphology.

As stated previously, dissection is a function of both wall stress and the forces between wall lamina.

Therefore, it is intuitive that peak wall stress alone is not an adequate marker for this condition. Instead, dissection may be better indicated by wall shear stress, delamination strength, changes in local microarchitecture, or a host of other factors.

Nevertheless, future studies using more accurate reporting of dissection locations and modeling features (heterogeneous wall thickness and correct zero-pressure geometry) are needed to confirm these results.

REFERENCES [1] Coselli et al. Tex heart inst J. 38.6 694-700, 2011 [2] Pape et al. Circulation 116 1120-1127, 2007 [3] Elefteraides, Ann thorac surg 74.5 1877-1880, 2002 [4] Azadani et al. Ann thorac surg 96.1 50-58, 2013 [5] Saliba et al. Int J cardiol heart vasc 6.1 91-100, 2015 ACKNOWLEDGEMENTS Dissection sites were identified by Leonid Emerel, MD. Training for 3D reconstruction and Abaqus was provided by Joseph E. Pichamuthu, ME, MS. Funding for this project was provided by the Swanson School of Engineering and the Office of the Provost. Special thanks to Tim Chung for his assistance in creating this abstract.

Figure 2: R2 values for a 1:1 relation between stresses at consecutive time points

Assessment of Human Stem Cell Retention and Host Cell Invasion in an Implanted Seeded Tubular Scaffold Abigail M. Snyder1, Katherine L. Lorentz1, Antonio D’Amore1, Justin S. Weinbaum1,2, William R. Wagner1,2,3, and David A. Vorp1,2,3,4,5 Departments of Bioengineering1, Surgery3, Cardiothoracic Surgery4, and Chemical and Petroleum Engineering5; McGowan Institute for Regenerative Medicine2, University of Pittsburgh, PA, USA Email: ams528@pitt.edu, Web: http:// engineering.pitt.edu/vorplab/ INTRODUCTION Cardiovascular disease is currently the primary cause of death worldwide. Mortality numbers are continuously rising each year, amounting to an alarming 23.6 million predicted deaths worldwide by 2030 [1]. When an insufficient blood supply to the heart or lower limbs is seen, as is the case with narrowing and/or atherosclerosis of the coronary artery, revascularization is required. The most common revascularization procedure is a coronary artery bypass surgery which uses an autologous graft as the bypass conduit. Current revascularization graft options are less than optimal, often leading to thrombosis and hyperplasia, thus requiring additional surgeries for the patient [2]. In particular, the autologous graft mentioned above requires a secondary surgery to harvest the graft, which not only significantly increases the time of the procedure, but also increases the potential for infection at the harvest site [3]. A clinically-viable tissue engineered vascular graft (TEVG) would fill the need for a suitable revascularization graft.

The Vorp lab combines the biologic and synthetic approach by seeding human mesenchymal stem cells (MSCs) into a biodegradable, biomimetic scaffold.

MSCs offer several advantages over primary cells such as their ease of isolation, self-renewal capacity, differentiation potential, and ability to secrete a wide spectrum of factors with varying functional effects [4]. After 8 weeks of in vivo remodeling, the seeded scaffold becomes a vessel-like TEVG. As a measure of primary success, the TEVG remains patent over the 8 week period, but it also changes composition as evidenced by the presence of new rat endothelial cells, smooth muscle cells, collagen, and elastin.

Notably, the cells which were present in the seeded scaffold no longer remain at the end of 8 weeks.

The fate of the seeded MSCs is unclear. It does not appear that the MSCs transdifferentiate into vascular cells, rather the evidence points to these cells being critical mediators of host cell recruitment [5]. There is a critical need to obtain a more specific time frame of when the seeded cells and their important

paracrine recruitment factors leave as the native cells accumulate in the graft. We hypothesize that the seeded MSCs depart the graft during the first 4 weeks post-implant, corresponding to the time host cells repopulate the scaffold.

METHODS Utilizing a rotational vacuum seeding device, adult MSCs (RoosterBio) were seeded into a biodegradable, bilayered, elastomeric tubular scaffold based on the polymer poly(ester urethane)urea (PEUU). The PEUU is first formed into a porous inner layer using thermally induced phase separation, to support cell seeding and integration into the pores [1]. PEUU is then utilized to form a denser electrospun outer layer that mimics the native arterial mechanical properties. A 48 hour dynamic culture period was included to allow cells to bind to the scaffold prior to implantation (in vivo flow conditions). The seeded scaffold was then implanted into the infrarenal abdominal aorta of a Lewis rat. After 1 or 4 weeks in vivo (n=1 and 3, respectively) angiography was performed to assess patency, and then the TEVGs were explanted.

Explanted TEVGs were fixed in paraformaldehyde, soaked in 30% sucrose, then frozen down using OCT media(Fisher HealthCare, Huston TX). The frozen TEVGs were sectioned to a thickness of 9 µm and were mounted on gelatin-coated slides [1]. After sectioning, the samples were stained using immunofluorescent chemistry for human nuclear antigen (HNA), alpha-smooth muscle actin(αSMA), calponin (to mark late stage smooth muscle cells), and von Willebrand factor (vWF, to mark endothelial cells). Imaging was completed at both 10x and 20x using an epifluorescence microscope and its corresponding NIS Elements software (Nikon). The desired images were quantified for the presence of positive DAPI (total cell count) staining using ImageJ software. The images were then manually quantified for the presence of positive HNA, αSMA and calponin markers. By comparing the quantified HNA, αSMA and calponin results to the total cell count, we were able to find the percentage of human

and late stage smooth muscle cells within our graft at the different time points.

RESULTS TEVGs were observed to show 100% patency at 1 week (n=1) and 4 weeks (n=3) post-implant.

Immunostaining was positive for the vWF stains at both 1 and 4 weeks post-implant (Fig. 1 illustrates the presence of all four markers in a 4 week TEVG).

An apparent decrease in the percentage of vascular cells that were HNA positive was observed from 1 to 4 weeks (from ~10 to 2.5%, respectively, see Fig. 2).

Similarly, the percentage of vascular cells that were αSMA positive apparently decreased (from 13.1 to 9.4%, respectively). An apparent increase in the percentage of cells that were calponin positive was also observed from 1 to 4 weeks (from 0 to 21.1%, respectively).

DISCUSSION

Fig. 1. Staining and imaging of a MSC 4 week explant. a) Positive HNA staining (red) and positive DAPI staining (blue). b) Positive staining for calponin (red), vWF (green) and DAPI (blue). c) Positive staining for αSMA(red) and positive DAPI staining (blue).

The positive patency results are promising, showing that the TEVGs are not demonstrating signs of acute thrombosis at this point during the remodeling process. The hypothesis stated above was supported in that a qualitative loss of seeded human cells was observed between the 1 week and 4 week time point.

It was previously believed that the majority of seeded cells would completely evacuate the graft after 2 days following implantation [5]. Since the HNA results show the presence of human cells still remaining in the graft as late as 4 weeks, this may indicate a prolonged role for the seeded MSC as active modulators of host cell remodeling or thrombosis. An example of the progressive host cell remodeling can be seen in both the αSMA and

Fig. 2. Graphical display showing the results of HNA, αSMA and calponin at both 1(blue) and 4(grey) weeks.

calponin results mentioned above. The presence of αSMA without calponin in the 1 week explant shows that the smooth muscle cells are maturing and continually migrating into the graft. Partial discontinuity of the vWF shows that although a complete endothelial layer is not yet seen in the graft, the presence of endothelial cells was demonstrated as early as the 1 week time point.

Endothelization along with the increasing smooth muscle cells and late stage smooth muscle cells demonstrate the successful preliminary stages of remodeling, primarily the infiltration of host cells into the TEVG. Along with data already generated for 8 week explants [1], to continue the progress with this characterization more samples need to be collected at the 1 and 4 week time points, as well as obtaining data from a 6 week time point. After the collection and analysis of the data is completed we will have a more robust idea of when the paracrine recruitment factors leave and native host cells migrate in during these 8 weeks of remodeling.

REFERENCES 1. Krawiec, J. T., el al. Tissue Eng Part A 22(9-10): 765-775. 2016.

2. Krawiec, J. T., el al. Biomaterials 33(12): 33883400. 2012.

3. Daenens, K., et al. Eur J Vasc Endovasc Surg 25(3): 240-245. 2003.

4. Krawiec, J. T., et al. Tissue Eng Part A 21(3-4): 426-437. 2015.

5. Roh, J. D., et al. Proc Natl Acad Sci U S A 107(10): 4669-4674. 2010.

ACKNOWLEDGEMENTS I would also like to acknowledge funding from Dr. David Vorp, the Swanson School of Engineering and the Office of the Provost.

STIMULATION OF ELASTIC FIBER PROTEINS BY MESENCHYMAL STEM CELL-DERIVED FACTORS Rachel Sides1, Kaori Sugiyama7, Aneesh Ramaswamy1, David Vorp1,2,3,4,5,6, Hiromi Yanagisawa7, and Justin Weinbaum1,4 1

4 Dept of Bioengineering McGowan Institute for Regenerative Medicine 2 5 Dept of Cardiothoracic Surgery Center for Vascular Remodeling & Regeneration 3 6 Dept of Surgery Dept of Chemical & Petroleum Engineering University of Pittsburgh, Pittsburgh, PA, USA 7

Tsukuba Advanced Research Alliance Center University of Tsukuba, Japan

Email: res136@pitt.edu Web: http://saggymouse.tara.tsukuba.ac.jp/en/ INTRODUCTION Many diseases are the result of malformations in the extracellular matrix (ECM) and matricellular proteins that comprise elastic fibers. Examples include Williams syndrome (elastin), Marfan syndrome (fibrillin-1), and cutis laxa (fibulin-5). In the context of aortic aneurysm, mesenchymal stem cells (MSCs) have shown the ability to preserve elastic fibers in murine elastase-induced aneurysm models1.

In order to investigate the effect of MSCs on elastic fiber formation in vitro, three-dimensional tissue constructs were developed. The goal of this study was to determine if elastin production by smooth muscle cells (SMCs) deficient in various elastic fiber components would be elevated in response to MSC-derived secreted factors (MSC SF).

Additionally, we investigated whether elastin organizational matricellular proteins were impacted by this MSC SF treatment.

METHODS Cell Culture SMCs were purchased from ATCC (adult human aortic SMC, #PCS-100-012) or isolated as primary cultures from the aortas of 2-5 week-old wild-type mice in the C57BL6 background. MSC SF was collected from human adipose-derived MSCs cultured between passage 0 to passage 2 for 24-72

hours. 3D fibrin-based tissue constructs were prepared from a solution of fibrinogen (33.3 mg/ml, Sigma), thrombin (25 U/ml, Sigma), and the cells of interest (1x105 cells/construct). Constructs were cultured in the presence of fibrinolytic inhibitor, aminocaproic acid (ACA, 15 mM) and, when appropriate, MSC-SF in 1:1 ratio with SMC growth-supplemented medium (Cell Applications, #311K-500).

Indirect Immunofluorescence Samples were fixed using ice-cold methanol and blocked in a 50/50 Tween and cold water fish gelatin solution (Aurion, #900-033). Target proteins were elastin (Elastin Products Company PR533, 1:1000), fibrillin-1 (438, 1:50 and 9543, 1:100), and fibulin-5 (R&D Systems MAB3095, 1:1000).

Mounted samples were imaged using a Zeiss LSM 800 microscope.

Real-time PCR Samples were frozen in liquid nitrogen and then crushed. RNA was extracted using a Qiagen RNAeasy Mini Kit. cDNA was synthesized by priming for 5 minutes at 25 oC, reverse transcription for 20 minutes at 46 oC, and reverse transcriptase inactivation for 1 minute at 95 oC. Tropoelastin, fibulin-4, fibulin-5, and lysyl oxidase (LOX) were amplified using purchased primers (Sigma).

GAPDH was the reference gene to which all samples were normalized.

RESULTS

Figure 1. Elastic fiber formation in human SMCs cultured for 20 days without (A, C) or with (B, D) MSC conditioned media. Nuclei are blue, elastin is red, and fibrillin-1 (A, B) or fibulin-5 (C, D) is green.

Untreated SMCs produced elastic fibers after 20 days of culture (Figure 1). Elastin (red), fibrillin-1 (green in Figures 1A & 1B), and fibulin-5 (green in Figures 1C & 1D) were all detectable by indirect immunofluoresence, with a qualitative increase in all three proteins when stimulated with MSC-SF. Real time quantitative PCR (qPCR) analysis demonstrated that fibulin-5 and LOX expression increased with application of MSC-SF, while tropoelastin and fibulin-4 results were inconclusive (Figure 2).

Figure 2. Tropoelastin, fibulin-4, fibulin-5, and LOX expression in human SMCs cultured for 20 days with (yellow) or without (grey) MSC conditioned media as measured by qPCR normalized to GAPDH. Error bars indicate intra-sample variability.

Preliminary studies supported the viability of wildtype mouse SMCs in constructs, but elastic fiber formation was not observed using elastin and fibulin-5 fluorescence markers. Qualitatively, the mouse SMCs exhibited lower fibrin construct degradation than the human SMCs.

DISCUSSION The results of the indirect immunofluorescence and qPCR suggest that MSC-SF increases fibulin-5 and LOX expression and potentially increases tropoelastin production in human SMCs. Based on these promising results, future studies will look at insoluble elastin deposition to determine if the increased fibulin-5 and LOX expression results in more crosslinking between tropoelastin.

Additionally, although mouse SMCs did not form fibers, previous reports have suggested that fibrin degradation products assist with ECM production

by SMCs2. Thus, the lower fibrin degradation rate that was observed in the mouse SMCs may be contributing to the absence of fiber formation.

Future studies will look at the effect of varying ACA concentrations for culture of primary mouse SMCs. Overall, culturing human SMCs in threedimensional tissue constructs allows for proper cell growth and elastic fiber formation, and this elastic fiber formation is enhanced in the presence of MSC-SF. Initial studies with primary mouse SMCs failed to show elastic fiber formation but lay the foundation for future work. Ultimately, this work will allow for 3D studies of elastic fiber formation in disease models generated from genetically modified mice or patients with elastic fiber mutations.

REFERENCES 1. Blose, K. J. et al. Regen. Med. (2014). 9(6), 733741.

2. Ahmann, K. A. et al. Tissue Eng Part A. (2010).

16(10), 3261-3270.

ACKNOWLEDGEMENTS The authors would like to acknowledge funding from the International Studies Fund, the Swanson School of Engineering, and the Office of the Provost at the University of Pittsburgh.

The Development of a Mg Ring for the Regeneration of a Torn ACL for Human Application Ian Moran, Jonquil Mau, Savio L-Y. Woo Musculoskeletal Research Center, Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh Ijm8@pitt.edu INTRODUCTIONS The anterior cruciate ligament (ACL) is a major stabilizer of the knee that restricts anterior motion of the tibia with respect to the femur, as well varus-valgus, and internal-external rotation.

In the U.S., there are 200,000-250,000 ACL injuries per year and two-thirds of these injuries undergo reconstruction surgery. Though ACL reconstruction has been the gold standard for treatment of ACL injuries, there are short-tem complications associated with reconstruction including donor site morbidity and limited motion, as well as the long-term risk of osteoarthritis. We have developed and tested a promising new technique for healing the ACL by combining mechanical and biological augmentation strategies. This technique uses extracellular matrix scaffolds to accelerate new tissue growth along with a Mg ring that assists this healing process by bridging the gap between the torn ends of the ACL and loading the ligament throughout the healing process.

The Mg ring device was tested in vitro in a goat model and this research aims to modify the geometry of the Mg ring to fit the human ACL.

Figure 2. Figure A shows attachment of repair and fixation sutures to the ACL, figure B shows fixation and implantation of the ring.

METHODS Literature values for the geometry of the human ACL showed that it was necessary to have three sizes for the Mg ring to fit a human ACL, which can vary substantially in size. Based on the wide range of anatomical measurements of the human ACL found in literature, the Mg ring device was scaled into three sizes. They were modeled in SolidWorks (Waltham, MA). The smallest was 7 mm in diameter on the femoral side and 8.5 mm on the tibial side, the medium side was 8 mm on the femoral side and 9.5 mm on the tibial side, and the largest ring was 8.5 mm on the femoral side and 10 mm on the tibial side.

The models were then given a thickness of 1 mm to allow them to be printed with polylactic acid (PLA). These prototypes were then placed into 4 human cadavers knees by transecting the mid-substance of the ACL and implanting them to confirm that the rings diameter sizing was appropriate, as well as ensuring that the 7 mm height would not be a problem. Using FEBio (Salt Lake City, UT), the finite element method was used to ensure that the Mg ring designed for the human ACL could withstand loading for implantation without failure. After the rings were modeled and exported from SolidWorks, a mesh of 60,000 elements and 175,000 nodes was applied to the surface of each and uploaded to FEBio. A force of 40 N was applied to each of the four fixation suture holes where the sutures would contact the ring. An inward force of 20 N directed towards the central axis was also applied to the space between the edge of the ring and the suture holes in order to simulate the initial loading conditions during surgery.

RESULTS SECTION The 3D printed prototype well into the four cadaveric specimen. The small ring fit three specimens where both ends of the transected ACL fit fully inside the prototype and could be implanted into the articular space of the knee.

The fourth specimen was a larger leg, which required the use of the large ring and similar results were observed with the other specimen.

The results of the finite element analyses showed, the range of the effective stress was 108 to 188 MPa when the Mg ring was loaded as previously described, with the highest effective stress being the largest ring. The yield strength of the AZ31 a common Mg is 293 MPA, which is much higher than then the largest observed effective stress.

Discussion The implanted prototypes fit well in the four specimens that we had. However, the lack of variation in dimensions and small sample size were limitations of the study and do not represent the people that would most likely bee receiving ACL reconstruction. More cadavers should be used to ensure correct sizing of the rings. The ACL of these patients was also cut at the mid-substance, which allowed for the 7 mm height to not be an issue. The three prototypes for the Mg ring were then evaluated using finite element analysis. The maximum effective stress is lower than the yield strength of Mg alloy.

Thus, it can be concluded that the Mg ring design is suitable for implantation in the human knee.

References Farraro, et al. 2014, Farraro e al. 2016, C.R. Wheeless, III, 2013, C.D. Harner, et al.1995, Nicolas Pujol et al. 2012 ACKNOWLEDGEMENTS I would like to thank the University of Pittsburgh Musculoskeletal Research Center as well as the Swanson School of Engineering for funding my research. I would also like to thank Huijun-Kang for performing the surgeries.

Figure 1. Is an image of the effective stress on the ring at the maximum load described above.

EXPLORING SINGLE CELLED hPSC VIABILITY USING ALGINATE HYDROGELS Fatimah Adisa, Thomas Richardson, Ph.D, Ipsita Banerjee, Ph.D Banerjee Lab, Chemical and Petroleum Engineering Department University of Pittsburgh, PA, USA Email: fya3@pitt.edu

Before hPSCs can be manufactured on a large scale, research must first focus on preventing or minimizing dissociation-induced hPSC cell death.

Dissociation-induced apoptosis of hPSCs occurs when these cells lose cell-cell contact. Currently, single cell hPSC death is minimized by treating the cells with a soluble chemical; however, this only results in about 30% cell survival. Current research in our lab focuses on the use of peptides, molecules smaller than proteins, consisting of short chains of amino acids, to prevent this cell death. In order for these peptides to be effectively presented to the hPSCs during cell culture and growth, they must be attached to a supportive substrate. In this case Alginate hydrogels were used as a supportive substrate to simulate the use of a 3D platform.

METHODS hPSCs, specifically human embryonic stem cells (hESCs), were cultured and harvested in mTeSR1 media and then encapsulated in an alginate hydrogel bead, a polysaccharide derived from algae [2]. The hydrogel beads were modified with a peptide concentration of 1 mg peptide / g Alginate [3].

Using carbodiimide chemistry, EDC and NHS,

chemical factors used to conjugate the peptide, were used in a 2:1 molar ratio where .2 g EDC / g Alginate was used. Peptides used in this research are HAV10, ADT10, HAV6, and ADT6.

Assays were performed to quantitatively and qualitatively analyze cell viability. Qualitatively, LIVE/DEAD assays were performed so that cell viability and death could be visualized using fluorescent imaging. Quantitatively, Polymerase chain reaction (PCR) was done to ensure that the hPSCs maintained their pluripotency by checking for gene markers. The MTS assay was also used to measure cell proliferation.

RESULTS Qualitative analysis of the hydrogels were performed on day 1 and day 6. Figure 1 shows Live/Dead staining of hESCs in the hydrogel beads.

The HAV10-conjugated hydrogel best supports hESC proliferation.

A. Alg Only

Alg + HAV10

Alg + ADT10

Alg + HAV6

Alg + ADT6

LIVE/DEAD

INTRODUCTION Human pluripotent stem cells (hPSCs) have the ability to self-renew and become any cell type in the body through stage-wise differentiation mimicking development, making them ideal for drug discovery and treatment of several degenerative diseases such as Alzheimerâ&#x20AC;&#x2122;s and Type 1 Diabetes [1]. In both of these cases, the lack of fully functioning cells leaves the patient needing replacement cells. hPSC-derived cell therapy provides a potentially unlimited cell source for the treatment of these degenerative diseases. As a large number (up to 109 cells for treatment of type 1 diabetes) of hPSCs are required for the treatment of such diseases, current research is involved in finding efficient ways to produce hPSCs in a manner that avoids cell death and is scalable for bio-manufacturing.

Scale Bar: 450 Îźm

B. Alg Only

Alg + HAV10

Alg + ADT10

Figure 3: Pluripotency of cells in peptide-conjugated capsules were measured, normalized to alginate alone

LIVE/DEAD

In all, hydrogels were shown to support hESC pluripotency, meaning cells attached to those substrates maintained their differentiation potential Alg + HAV6

Alg + ADT6

Scale Bar: 450 μm

Figure 1: Live/Dead performed on hESCs in the hydrogels at 20x magnification, where green represents live cells and red represents dead cells. A) Hydrogels at Day 1 B) Hydrogels at Day 6

With time, the size of the cell colonies increases and more dead cells are visible.

Cell proliferation was also analyzed using the MTS assay. Seen in Figure 2, all of the peptideconjugated hydrogels supported cell proliferation when normalized to the alginate alone hydrogel.

Alg+Peptide/Alg only

Day 6 Proliferation 2 1.5 1 0.5 0 HAV10

ADT10

HAV6

ADT6

Figure 2: Proliferation of hESCS on hydrogels conjugated with peptide normalized to hydrogels with alginate alone

Pluripotent stem cell markers, Nanog and OCT4, expressions were measured and normalized against alginate only (Figure 3).

Nanog

OCT4

1

1

0.5

0.5

0

0 ADT6 HAV6 ADT6 ADT10

ADT10 ADT6 HAV6 ADT6

DISCUSSION Overall, the higher sequenced peptide-conjugated hydrogels (ADT10, HAV10) better supported hESCs and their proliferation. They showed strong initial and continued support of hESCs. These hydrogels also maintained the pluripotency of hESCs upon culture and encapsulation.

The use of alginate hydrogels as a tool for the transplantation of stem cells continues to be explored widely in the field of tissue engineering [2]. Identifying the best peptide for use in an alginate hydrogel presents a variety of paths on which future research could take. Such paths include, but are not limited to the in vivo use of these hydrogel capsules and identifying any synergistic effects that come from combining peptides at different concentrations.

REFERENCES [1] Zhu, Z., Huangfu, D., “Human pluripotent stem cells: an emerging model in developmental biology”, Development (2013) 140: 705-17.

[2] Lee, K.Y., Mooney, D. J., “Alginate: Properties and biomedical applications”, Progress in Polymer Science (2012) 37: 106-126 [3] Dhoot, N.O., Tobias, C.A., Fischer, I., Wheatley, M.A., “Peptide-modified alginate surfaces as a growth permissive substrate for neurite outgrowth” Wiley InterScience (2004) : 191-200 ACKNOWLEDGEMENTS I would like to extend my thanks to the Swanson School of Engineering and the Office of the Provost for supporting my research. I would also like to thank Dr. Ipsita Banerjee and Dr. Thomas Richardson for making this experience one in which I learned from.

Predicting Phase Behavior of Organic–Salt–Water, Two-Phase Systems using the AIOMFAQ Model Forrest Salamida, Giannfranco Rodriguez and Dr. Eric Beckman Beckman Lab, Department of Chemical Engineering University of Pittsburgh, PA, USA Email: fms11@pitt.edu, Web: www.engineering.pitt.edu/Departments/Chemical-Petroleum/ INTRODUCTION The current methods by which the desalination of water is achieved are energy inefficient. The two most common methods of desalination are distillation and reverse osmosis (RO), the latter of which requires facilities where energy consumption accounts for nearly 50% of operational costs (Seawater Desal…, 2011). Yet, distillation is no better; only 15% of the bottled water operators in the industry use distillation in comparison to the nearly 40% who use RO due to lower costs (Kucera, 2005). These conditions have led researchers on a quest for more efficient alternatives.

The scope of this project is to determine the feasibility of using reactive chemical extraction to desalinate water. This new method of desalination will use less energy than currently required and increase the availability of clean and safe drinking water. For it to work, an organic compound with the following qualities must be designed: 1) Reversibly reacts with water under reasonable conditions (temperature and pressure) 2) Impedes the transfer of salt across the water-organic phase barrier The scope of this paper is to detail the computer model built to predict the phase behavior of organic-salt-water mixtures. It will act as a tool in the search for organic compounds that repel salt.

The advent of computer modeling has expedited the design phase for the creation of a chemical process by allowing a user to run multiple iterations of a program while simultaneously having the functionality to vary chemical structure. This shifts the focus of research efforts for viable candidates from broad molecular structures to specific numbers and types of functional groups by improving a molecule incrementally.

Figure 1: The functional groups that were parametrized in the AIOMFAC model (Zuend, 2008)

METHODS The Universal Quasichemical Functional group Activity Coefficients (UNIFAQ) model was developed in 1975 by Freudensland to explain the phase behavior of organic compounds (Freudensland, 1975).

By combining thermodynamics and empirical measurements of multi-organic component-systems, Freudensland and his team determined the effect of single functional groups on the entire chemical behavior of a molecule when introduced to a mixture.

This was achieved by giving each pair of functional groups two asymmetric interaction parameters; one that described how functional group A affects functional group B, and another that describes how functional group B affects functional group A. This model is still used in petrochemical industries to predict the phase behavior for the multitude of products that appear during the process of cracking crude oil.

In 2008, Zuend expanded the UNIFAC model by developing the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) model (Zuend, 2008). The AIOMFAC model describes tropospheric aerosol behavior. In studying atmospheric composition, Zuend et al. successfully modeled inorganic component

behavior by determining how mixtures behave when introduced to salts. He also improved the accuracy of the parameters that describe functional groups not commonly found in crude oil such as alcohols.

Although developed to study atmospheric composition, the AIOMFAC model can be applied to a myriad of organic-inorganic-water-multi phase systems, allowing for the study of salt-waterorganic two-phase equilibrium.

With use of the AIOMFAC model, a program was built to explore the settling of mixtures containing water, sodium, chloride and an organic molecule that is designed by a user. The user also determines the temperature of the system and the mole fraction composition of the initial mixtures components.

RESULTS Binary phase diagrams of water-organic systems were generated to compare with literature data. This included the behavior of water when mixed with alkanes, mono and di-ols, carboxylic acids, and ketones. In addition to the functional groups needed to build these simple organic compounds, a few modifying functional groups were added to the program as well, including fluoro, chloro, nitro and nitrile groups.

It was found that alkyl-water behavior was modeled with a high degree of accuracy within the program.

However, the interaction parameters governing hydroxyl-water, and ketone-water behavior resulted in phase diagrams that predicted a higher favorability between water and organic compounds containing hydroxyls and/or ketones than exists in reality.

This means that phase diagrams generated by the program involving these molecules indicated that more water would be present in the organic-heavy phase than what is observed in the literature.

DISCUSSION Due to the asymmetric, multi-variable nature of the AIOMFAC model, it is impossible to tell which direction to change individual interaction parameters to increase or decrease favorability. It is also difficult to determine how these changes may affect the model’s accuracy when more complex organic molecules are introduced to the system.

Complicating matters further is that all interaction parameters used in the AIOMFAC model were globally fit to all literature data, including systems unrelated to the team objective. For example, some literature data used included pressurized vapor liquid equilibrium diagrams.

These factors result in less accurate phase diagrams for this specific application. One example of this occurred during the prediction of phase behavior involving geminal diols. The alcohol-water interaction parameters were determined with data sets that only considered organic molecules that had terminal diols. Therefore, when generating phase diagrams, the program chose to view the hydroxyl groups as being at either ends of the molecule rather than next to one another, as is the case with geminal diols.

CONCLUSION The program’s interaction parameters must be adjusted to reflect the behavior of systems more closely related to those that are of interest to the team. Therefore, the hydroxyl-water, and ketonewater interaction parameters will be fit using multivariable optimization methods in conjunction with literature data for binary liquid-liquid systems such as butanone – water.

As a future endeavor, it is also of interest to obtain literature data describing the phase behavior of less common ionic-organic pairs. This would allow for the modeling of more unique organic compounds that have the ionic characteristics required for the chemical extraction of water.

REFERENCES 1. "Seawater Desalination Power Consumption." Watereuse.org. WateReuse Association, Nov. 2011. Web. 25 Aug. 2017.

2. Bruce Kucera. "Water Distillation." Water Quality Products. Water Quality Products, 26 Sept. 2005. Web. 25 Aug. 2017.

3. Fredenslund, A., Jones, R. L., and Prausnitz, J. M.: GroupContribution Estimation of Activity Coefficients in Nonideal Liquid Mixtures, AIChE J., 21, 1086–1099, 1975.

Atmos 4. Zuend, A., et al. (2008), A thermodynamic model of mixed organic-inorganic aerosols to predict activity coefficients, Atmos. Chem. Phys. 8, 4559-4593.

ACKNOWLEDGMENTS This research was funded by a gift from the PPG Foundation.

Fouling Resistant Membranes Using Catalytic CuO Nanoparticles Manish Kumar, Rajarshi Guha, Michael Geitner, and Nikhil Malik Penn State Chemical Engineering Laboratory, Department of Chemical Engineering Penn State University, PA, USA

INTRODUCTION Reverse osmosis (RO) and nanofiltration (NF) membranes are used for desalination, wastewater reuse, and industrial water recovery but suffer from high-energy usage despite large improvements in recent decades. Major reasons for high-energy usage include membrane fouling and concentration polarization (CP). Fouling is the time dependent deposition of organic macromolecules and particles, as well as the growth of bacterial biofilms on membranes. CP is the accumulation of rejected solutes on the membrane, which reduces the driving force for filtration. We demonstrate a simple, nanoparticle-based, in situ approach of inducing chemical reaction-based micromixing on the membrane surface that can simultaneously eliminate fouling and concentration polarization. [1] Commercial desalination membrane surfaces were modified with the bioinspired adhesive polymer, polydopamine, and catalytic metal oxide nanoparticles (CuO) The oxygen molecules and hydroxyl radicals generated degraded organic matter and efficiently prevented particle and cell deposition through bubble-generated mixing while causing no observable membrane damage. The reaction generated convection also enhanced solute back diffusion mass transfer coefficients by more than an order of magnitude, resulting in nearcomplete elimination of CP. This simple, scalable, in situ approach could counter multiple membrane foulants simultaneously and mitigate CP, resulting in considerable energy savings. Despite large advances in membrane materials development, high pressure membrane processes suffer from performance deterioration of membranes and high energy consumption. Two persistent issues in these membrane systems that increase energy consumption and contribute to increased operational costs are: 1) concentration polarization (CP) where solute build up on the membrane surface causes enhanced osmotic pressure and reduces the driving

force for transport of water while at the same time, increasing the driving force for passage of contaminants, and 2) fouling, where colloidal particles, organic matter, and microbes deposit on membranes leading to increase in total membrane resistance and observable performance deterioration in these systems. Indeed, Elimelech and Phillip have recently argued that the efficiency of current membrane materials is approaching its thermodynamic limit for seawater desalination and the further gains in efficiency can only be achieved by improving system and operational design including better pretreatment, minimization of CP, and mitigation of fouling. CP development is almost instantaneous and is exacerbated by deposited foulants that can trap dissolved solutes. CP is so pervasive that it is considered a given during operation and its mitigation less researched than fouling mitigation. Currently commercialized solutions for CP mitigation require a redesign of current membrane infrastructure with rotating or vibrating modules. We propose a simple technique to address both CP and fouling challenges by an situ approach. [1] METHOD Flat sheet seawater RO membranes (DOW SW30HR) and were obtained from Dow Water and Process Solutions (DWPS) and were used for colloidal/organic fouling and biofouling experiments, respectively. Dopamine hydrochloride was polymerized in 10 mM Tris-HCl buffer maintained at pH ~ 8.5 and coated on respective thin film composite membranes (TFC) under continuous rocking conditions. CuO nanoparticles were prepared at room temperature using drop-by-drop addition of NaOH to a Cu(NO3)2.2H2O precursor solution in ultrapure water. The modified membranes are referred to as 80 ppm CuO/PDA based on precursor concentrations. [1]

RESULTS & DISCUSSION CuO nanparticles were synthesized in situ on commercial membrane using drop-by-drop method.

The experiment successful produced bubbles at the surface of the membrane with the H2O2 came in contact with the CuO nanparticles anchored on the reverse osmosis membrane. [1] We observed robust reversal of the flux decline during real time operation of a bench-scale RO system with the catalytic membrane upon addition of H2O2. This effect was observed with silica colloids, which is commonly used as model foulants. Specifically, with 17 liters per meters squared per hour (LMH) initial flux, 0.017% silica nanoparticles caused rapid fouling and decreased the normalized flux. Addition of 240 ppm H2O2 gave a 300% flux recovery. A normalized flux decline rate from fouling, and a flux recovery rate on addition of H2O2 was calculated to provide a measure of the real-time fouling reversal effectiveness of the proposed strategy.

Therefore, the flux recovery rate was almost 3 the time of the flux decline rate (figure 1). The control experiment, performed with only virgin (uncoated) SW30HR RO membranes, showed no observable effect of flux improvement if only DI water was added and it continued to decrease during the course of data collection. The catalytic approach is robust and also reproducible as shown with the multiple flux decline and recovery cycles using the same composition of silica foulants and H2O2. This is also an example of on demand flux decline elimination, since H2O2 can be injected at any point of time during the filtration process and the flux would recover rapidly to the prefouling level. [1]

We propose that the dominant forces on a free bubble, just separated from the surface, are buoyancy and electrostatics, acting toward and away from the membrane, respectively. These free moving bubbles on membrane surface can cause rapid mixing in the concentration boundary layer by entraining surrounding liquids to develop strong recirculation flows. Additionally, surface attached bubbles can impart adverse pressure gradients to crossflow and may generate recirculation wakes by a phenomenon known as separation bubbles. Apart from this micromixing induced disruption of particle deposition, strong repulsive van der Waals interaction of ~8 kT at the electrical double layer length scale in silica foulants-water-O2 bubble system may contribute as an additional mechanism. [1] Silica foulants also decreased the flux during standard operation without catalytic action, at a slower rate than silica nanoparticles. Both CuO/ PDA modified membranes and control membranes were fouled at similar rates and DI water addition did not result in flux improvement. Due to concomitant micromixing driven enhanced mass transfer near the membrane after H2O2 addition, the flux recovered rapidly as in case of CuO/ PDA modified membrane.

REFERENCES [1] Guha, Rajarshi, Boya Xiong, Michael Geitner, Tevin Moore, Thomas K. Wood, Darrell Velegol, and Manish Kumar. "Reactive micromixing eliminates fouling and concentration polarization in reverse osmosis membranes." Journal of Membrane Science 542 (2017): 8-17. Science Direct. Web. 27 Aug. 2017.

ACKNOWLEDGEMENTS Thank you Dr. Kumar for allowing me to do research and use the equipment in your lab at Penn State University. A special thanks to University of Pittsburgh for the gracious stipend

Figure 1: The recovery of flux after H 2 O 2 treatment

SEMI-AUTOMATED SEGMENTATION OF GLIOBLASTOMAS IN BRAIN MRI USING MACHINE LEARNING TECHNIQUES Naomi Joseph, Hongliang Ren, Parita Sanghani Department of Chemical Engineering (Department of Biomedical Engineering) University of Pittsburgh, PA, USA (National University of Singapore, Singapore) Email: nmj24@pitt.edu, ren@nus.edu.sg INTRODUCTION Glioblastomas are aggressive brain cancers, which originate from glial cells and are supported by a large network of blood vessels [1]. There are two types of GBMs: primary and secondary. Primary GBMs are more aggressive in nature and develop rapidly whereas secondary GBMs grow more slowly but can evolve into a high-grade tumor [2].

GBMs are diagnosed using MR images. For surgical planning, it is important to accurately segment and delineate the different pathological regions within the tumor on an MRI [3]. Different modalities like T1 (T1 pre-contrast), T1CE (T1 post-contrast), T2 and FLAIR (Fluid-Attenuated Inverse Recovery) are used for this segmentation as every modality provides different information regarding the tumor structure. Manual segmentation requires identification of the different tumor parts and labelling each part voxel-by-voxel, a process that is time taxing and subjective for clinicians.

Thus, extensive research has been conducted to develop and test semi-automated and automated techniques to aid physicians in the qualitative diagnosis of the glioblastomas [3].

The purpose of this project was to learn manual segmentation of GBMs using four different MRI modalities. Alongside, a semi-automated technique of segmentation was performed using K-means clustering on the BRATS 2017 patient data set. The clustering performance accuracy was measured using the Dice Coefficient.

METHODS A. Manual Segmentation

Manual segmentation was performed on The Cancer Genome Atlas (TCGA) data set of eighty-five patients. TCGA, the National Cancer Institute (NCI), and the National Human Genome Research Institute (NHGRI) collaborated to provide a public genomic data set for cancer research. Manually segmenting one patient took up to eighteen hours.

B. K-Means Clustering A semi-automated segmentation technique was performed on the GBM ROIs of the MRI scans.

This technique was tested on the Brain Tumor Segmentation (BRATS) 2017 data set publicly provided by the Perelman School of Medicine at the University of Pennsylvania. These scans and their labels, which have been manually revised by neuroradiologists every year, were considered the ground truths throughout this project. The BRATS 2017 defines 3 clusters: enhancing tumor, edema, and a merged necrosis and non-enhancing tumor.

Initially, the whole tumor region for each patient of the BRATS 2017 data set was delineated using the ground truth labels. This whole tumor mask consisted of all 4 ROIs as seen in Figure 1. This mask was binarized to isolate the whole tumor from the surrounding brain as shown in Figure 1. Kmeans clustering was performed within the whole tumor mask. Ten iterations of k-means clustering took two to three minutes per modality (Intel CORE i3 2.50GHz processor, with 6GB Ram).

Figure 1: (a) Original T1CE modality (b) BRATS 2017 ground truth segmentation (c) Binarized whole tumor ROI mask

RESULTS AND DISCUSSION The first part of this project was focused on manual segmentation of the 4 different pathological parts of the GBM on MRIs. Fig. 2 illustrates the axial slice of an MRI of a patient where the segmentation was performed and verified by a neurosurgeon at the National Neuroscience Institute, Singapore.

The dice coefficient analyzes the accuracy of the kmeans clustering technique with respect to the ground truth labels provided in the BRATS 2017 data set. Equation 1 illustrates the dice coefficient for all the ten selected patients.

Figure 2: (a) T1CE (b) T1 (c) T2 (d) FLAIR (e) Manual Segmentation on the T1CE modality where CET, NET, necrosis, and edema appear white, purple, yellow, and blue respectively

Manual segmentation is a tedious process and also leads to inter-expert variability. Hence, a semiautomated segmentation approach was performed using the k-means clustering algorithm to determine the labels of each voxel within the whole tumor ROI. Fig. 3 represents the axial slice of the MRI from four modalities of a patient along with the results of K-means clustering implementation.

Figure 3: (a) T1CE (b) T1 (c) T2 (d) FLAIR of a BRATS 2017 patient (e-h) Corresponding K-means Clustering Segmentation result with four clusters for the four modalities respectively.

The T1CE and FLAIR modalities of ten randomly selected patients underwent a k-means clustering for 2 clusters. The T1CE modality’s two clusters represented enhanced tumor and combined nonenhanced tumor and necrosis. FLAIR modality’s two clusters represented edema and the remaining whole tumor ROI. These two segmentation masks were merged to produce a final segmentation mask.

Fig. 5 illustrates an example of the axial slice of one of these final masks alongside its ground truth from BRATS 2017.

Figure 4: (a) T1CE (b) K-means Clustering Final Combined Mask (c) BRATS 2017 Ground Truth

Equation 1: Dice Coefficient

In Equation 1, A and Brepresents the number of elements in the ground truth’s enhanced tumor region and the k-means clustering final segmentation mask’s enhanced tumor region. The average Dice Coefficient calculated was 0.823.

One of the drawbacks of K-means clustering is that it randomly assigns its centroid points within the tumor ROI. This allows for MRI segmentation mask labels to differ between patients making it almost impossible to later merge the four modality masks to create a final simulated segmentation mask. The labels of the modality masks were manually entered into another simulation to merge the T1CE and FLAIR masks, and were qualitatively compared with the ground truths. The accuracy of k-means clustering for the enhancing tumor of the ROI is 82% on average via the dice coefficient. Therefore, it is beneficial to perform k-means clustering for this region of the tumor and then manually segment the remaining three regions of the tumor.

REFERENCES 1. Fyllingen et al. PLOS ONE, 11, 2016.

2. Simi et al. The Egyptian Journal of Radiology and Nuclear Medicine, 46, 1105-1110, 2015 3. Despotović et al.

Computational and Mathematical Methods in Medicine, 2015, 1-23, 2015 ACKNOWLEDGEMENTS This work was funded jointly by Dr. Little, the Swanson School of Engineering and the Office of the Provost.

MICROPARTICLE TREATMENT OF PERIODONTITIS: ANALYSIS OF THE EFFECT OF SEX HORMONES ON DISEASE OUTCOMES AND CORRELATED IMMUNE RESPONSE Kayla M. LeMaster, Ashlee C. Greene Little Lab, Department of Chemical and Petroleum Engineering University of Pittsburgh, PA, USA Email: kaylalemaster@pitt.edu INTRODUCTION Periodontitis is a disease initiated by the buildup of bacteria, plaque and tartar around the gingival tissue.

When the body’s immune system fights the bacteria, the adverse inflammatory response causes destruction of the alveolar bone and of the surrounding tissue. However, current management of the disease focuses on the mechanical removal of plaque and the use of antibiotics rather than targeting a modification of the catastrophic immune response.

Recently, regulatory T cells (Tregs), a type of immune cell, have been shown to be able to reduce periodontal inflammation by bringing the oral environment to homeostasis [1]. To take advantage of this effect, the Little Lab has identified the codelivery of three factors (TGF-β, IL-2, and rapamycin) as an effective approach to produce a local environment favorable for the induction of Tregs [2]. The focus of this project is to determine the effect a tri-factor controlled release microparticle system has on periodontitis in a murine model. TGFβ, IL-2, and rapamycin are encapsulated separately during microparticle fabrication and later administered to mice (TGFβMP, IL-2MP, and rapaMP, respectively). Specifically, the effects on male and female mice will be studied. Current literature suggests that when compared to their male counterparts, female mice’s sex hormones advance the pathology of periodontitis [3]. To explore this idea, the aim of this project is to examine differences in Treg induction and disease outcome that may be attributed to the hormonal environment of the female body.

MATERIALS AND METHODS The microparticles were fabricated as follows.

RapaMP were produced via the single emulsionevaporation technique using a homogenizer at 3000 rpm. 50 μl of rapamycin (Alfa Aesar, Haverhill, MA) was added to a solution of polylactic-co-glycolic acid (PLGA; RG502H, Sigma Aldrich, St. Louis, MO) in dichloromethane (DCM) then homogenized in 2%

polyvinyl alcohol (PVA) to create the oil-in-water emulsion.

TGFβMP and IL-2MP were formulated using the water-in-oil-in-water double emulsion-evaporation technique. This required the use of a sonicator at 25% amplitude for the initial emulsion and a homogenizer at 3000 rpm for the second emulsion. For the TGFβMP, 50 μl of recombinant human TGF-β (Peprotech, Rocky Hill, NJ) was added to a solution of polymers RG502 and mPEG-PLGA dissolved in DCM. The mixture was sonicated for 10 seconds then homogenized in 2% PVA. For the IL-2MP, 50 μl of recombinant mouse IL-2 (R&D Systems, Minneapolis, MN) was added to a solution of PLGA in DCM. The mixture was sonicated for 10 seconds then homogenized in a salt solution of 2% PVA containing 51.6 mmol NaCl. After homogenization, all batches were mixed into separate beakers of 1% PVA and stirred for 3 hours on ice. The particles were then isolated by centrifugation, washed with Milli-Q water, frozen in liquid nitrogen, and lyophilized. Between analyses, they were stored in a -20°C freezer.

ANALYSIS The morphology of the microparticles was characterized using scanning electron microscopy (SEM). The size of the microparticles was also measured using a volume impedance method via Coulter Counter. Microparticles were characterized for their release of drug over time; they were rotated in an incubator at 37°C and the release profiles were obtained as shown in Figure 1.

Male mice maxillae were dissected, defleshed and stained with methylene blue. The teeth were photographed under a microscope and measurements were performed using ImageJ software. The area between the cemento-enamel junction (CEJ) and the alveolar bone crest (ABC) was traced and measured for each set of teeth.

Shown in Figure 2 are average area measurements of the studied area of male maxilla for three separate groups. Group A was bacteria-induced diseased mice with no treatment, group B was bacteria-induced diseased mice with tri-factor microparticle treatment, and group C was mice that did not receive either bacteria-induced disease or treatment. The disease untreated mice have the largest average, as the area between the CEJ and ABC increases as the disease progresses and bacteria destroys the associated bone and tissue. The disease treated and the control mice have about the same average area, suggesting that the treatment successfully reversed the progression of the disease. As per a one-way anova test, there is no statistically significant difference between these two groups. To further investigate the difference between them regarding progression of disease, the disease will need to be monitored via a swab test and the use of PCR to quantify bacterial levels.

Due to time constraints, only the male mice portion of this study was completed. Female mice have yet to be studied and will be the focus of the next study.

Due to the success of the male study, the above methods will be reproduced and the same conditions will be met during the female study in order to correctly compare any differences on disease outcome that may be due to the presence of female sex hormones.

Cumulative Release (ng Rapa/mg MP)

4000 3000 2000 1000 0 0

10

20

Time (days)

TGF-β and IL-2 Release Profiles Cumulative Release (ng drug/mg MP)

The release profiles obtained after 23 days for rapaMP or 30 days for TGFβMP and IL-2MP are shown in Figure 1.

Rapa Release Profile

TGFB IL2

8 6 4 2 0 0

10

20

30

Time (days)

Fig. 1. Release profiles of microparticles.

ABC-CEJ Area Measurements Average overall area (square μm)

RESULTS AND DISCUSSION On average, TGFβMP, IL-2MP and rapaMP were 17.14 μm, 25.78 μm, and 12.89 μm in diameter, respectively. Each type of microparticle also varied in morphology; rapaMP were spherical without pores, TGFβMP were non-spherical without pores, and IL-2MP were spherical with pores due to differing fabrication conditions. The IL-2MP used PVA containing 51.6 mmol NaCl, forming a porous structure as the osmolarity difference pushed water into the spheres. The TGFβMP were produced with two polymers: RG502 and mPEG-PLGA, causing the microparticles to form in a non-spherical fashion.

In contrast, the rapaMP did not require any additions to polymer or PVA, explaining the smooth, spherical surface structure.

A - Disease Untreated B - Disease Treated C - Age Control

500000 400000 300000 200000 100000 0

Fig. 2. Area measurements obtained through ImageJ analysis of microscopic images.

REFERENCES 1. Glowacki et al. Proc Natl Acad Sci USA 110, 18525-18530, 2013.

2. Jhunjhunwala et al. J Controlled Release 159, 78–84, 2012.

3. Shusterman et al. BMC Genet 14, 68, 2013.

ACKNOWLEDGEMENTS Funding was jointly provided by Dr. Steven R. Little, the Swanson School of Engineering at the University of Pittsburgh, and the Office of the Provost.

MODELING INTERFERON RESPONSE IN PANDEMIC H1N1 INFLUENZA VIRUS INFECTED MICE USING GENE EXPRESSION DATA Kyler R. Madara and Jason E. Shoemaker The Shoemaker Immunosystems Laboratory, Department of Chemical and Petroleum Engineering University of Pittsburgh, PA, USA Email: krm110@pitt.edu, Web: https://krm110.wixsite.com/kyler-madara-website INTRODUCTION Innate immune response is essential for viral clearance during infection. However, there are drawbacks to this response. Inflammation caused by cytokines, such as interferon, can cause adverse and sometimes deadly effects [1]. Developing an engineering model of the interferon response dynamics can help researchers understand the potential drawbacks of a powerful immune response.

The purpose of this project is to model the inflammatory interferon response to pandemic H1N1 (pH1N1) influenza virus infection in mice using gene expression data.

principle component of the gene expression matrix) was used to describe gene expression dynamics.

Matlab was used to generate the model shown in Tables 1 and 2. The model consists of 4 ordinary differential equations (ODEs) and 9 parameters.

Each equation adheres to biological principles and mass-action kinetics. The 4 species in the model are target cell fraction (T), infected cell fraction (c), viral load (v), and interferon (i). Target cells decrease as they are infected by the virus and also decrease as they naturally die. Infected cells will increase at the same rate that target cells become infected, but will then decrease as they lyse and release more virus.

METHODS Gene expression data and experimental conditions were previously reported [2]. Three mice were humanely sacrificed at each time point to collect lung infection data; in total, 168 mice were sacrificed.

Gene expression data was averaged at each time point. Samples from mock-infected, time-matched animals served as controls.

To cluster the genes, weighted correlation network analysis (WGCNA) was performed [3]. After clustering, DAVID Gene Ontology Tool was used to determine which clusters are associated with interferon production. From this analysis, Module (cluster) 4 was found to be the most enriched in interferon production, inflammation, and immune response (p-value = 10-3.8). The eigengene (first

Figure 1: The experimental (blue) and simulated profiles (black). The error for the simulation was 5.0791. (Time Bounds: 0 to 168 hours post infection).

Table 1: Model Equations, Descriptions, and Initial Conditions

Equation

Description Start

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Target Cells

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Infected Cells

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Virus Growth

4.3985

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Interferon Production

0

Table 2: Model Parameters Parameter Value Units đ?&#x2019;&#x152;đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;&#x2021;đ?&#x2019;&#x2020;đ?&#x2019;&#x201E;đ?&#x2019;&#x2022; đ?&#x2019;&#x152;đ?&#x2019;&#x2026;đ?&#x2019;&#x2020;đ?&#x2019;&#x201A;đ?&#x2019;&#x2022;đ?&#x2019;&#x2030; đ?&#x2019;&#x152;đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;&#x2021;,đ?&#x2019;&#x2026;đ?&#x2019;&#x2020;đ?&#x2019;&#x201A;đ?&#x2019;&#x2022;đ?&#x2019;&#x2030; đ?&#x2019;&#x152;đ?&#x2019;&#x2014;,đ?&#x2019;&#x2018;đ?&#x2019;&#x201C;đ?&#x2019;?đ?&#x2019;&#x2026; đ?&#x2019;&#x152;đ?&#x2019;&#x2014;,đ?&#x2019;?đ?&#x2019;&#x2020;đ?&#x2019;&#x2C6; đ?&#x2019;&#x152;đ?&#x2019;&#x2014;,đ?&#x2019;&#x2026;đ?&#x2019;&#x2020;đ?&#x2019;&#x201A;đ?&#x2019;&#x2022;đ?&#x2019;&#x2030; đ?&#x2019;&#x152;đ?&#x2019;&#x160;,đ?&#x2019;&#x2018;đ?&#x2019;&#x201C;đ?&#x2019;?đ?&#x2019;&#x2026; đ?&#x2018;˛đ?&#x2018;¨ đ?&#x2019;&#x152;đ?&#x2019;&#x160;,đ?&#x2019;&#x2026;đ?&#x2019;&#x2020;đ?&#x2019;&#x2C6;

0.002379 0.050347 12.05254 42.95610 0.004912 0.000276 104.8979 55.28594 0.058559

h-1 * log(PFU/g)-1 h-1 h-1 h-1 log(PFU/g)*h-1 h-1 h-1 log(PFU/g) h-1

The virus concentration will increase as the infected cells release more viral copies, but will decrease as interferon concentration increases and as the virus naturally dies. Cells will recognize foreign viral RNA and respond by producing interferon at a rate described by Hill kinetics.

The model was parameterized using FMINCON to minimize the simulation error found by comparing the simulation to the WGCNA-generated eigengene as well as the observed viral titers. The fitted model parameters and resulting dynamics are shown in Table 2 and Figure 1, respectively.

RESULTS As can be seen from Figure 1, the model simulates the experimental results well. Not only does the model follow the experimental results, but the inclusion of target cells and infected cells allows the model to â&#x20AC;&#x153;shut offâ&#x20AC;?. Figures 2 and 3 show this behavior. As the virus dies off over a longer period of time, the model stops interferon production, which adheres to biological principles of homeostasis.

Figure 3: Interferon Expression against Viral Titer for Iterations of Interferon Production (đ?&#x2018;&#x2DC;đ?&#x2018;&#x2013;,đ?&#x2018;?đ?&#x2018;&#x;đ?&#x2018;&#x153;đ?&#x2018;&#x2018; ). The red line represents the original parameter reduced 50%, while the purple line represents the original parameter increased 50%.

(Time Bounds: 0 to 1000 hours post infection).

replication. Figure 3 shows that changing the rate at which interferon is produced creates a heightened inflammatory response to viral titer. If the goal is to decrease inflammation, regulating interferon response would not work. As interferon production increases by 50%, maximum viral titer decreases by 3.75%, but maximum inflammation increases by 34.9%. Therefore, the decrease in viral titer is not worth the possibility of a more inflamed response, which could result in host death.

Future works for this model include sensitivity and bifurcation analysis to see what aspects of cellular dynamics effect viral infection the most. More sensitive parameters can be baselines for future drug targets and vaccines to prevent future outbreaks.

Figure 2: â&#x20AC;&#x153;Shut-offâ&#x20AC;? dynamics of the model against time.

(Time Bounds: 0 to 500 hours post infection).

Figure 3 also suggests a nonlinear sensitive interferon response to viral titer as interferon production rate changes, a result that would not have been found without mathematical modeling.

DISCUSSION Given the nonlinear relationship between inflammation and viral load, it may not be beneficial to regulate interferon production to limit virus

REFERENCES 1. Billiau Journal of Interferon Research 7, 559-67, 1987.

2. Shoemaker et al. PLoS Pathogens 11, 1-25, 2015.

3. Langfelder and Horvath BMC Bioinformatics 9, 2008.

ACKNOWLEDGEMENTS I would like to thank Dr. Jason E. Shoemaker for allowing me to work on this project during the Summer 2017 term. I would also like to thank the Swanson School of Engineering and the Office of the Provost for funding my project.

SIMULATING THE NATURAL GAS FILLING RATE OF FUEL TANKS PACKED WITH METAL-ORGANIC FRAMEWORK ADSORBANTS Keerthi Gnanavel and Christopher E. Wilmer Hypothetical Materials Laboratory, Department of Chemical Engineering University of Pittsburgh, PA, USA Email: kkg10@pitt.edu, Web: http://www.wilmerlab.com/ INTRODUCTION Alleviating the dependence on petroleum for transportation has been a global concern for decades. Achieving this goal would require a more balanced energy system that utilizes solar, wind, water, nuclear, and natural gas technologies.

The density of natural gas storage limits compressed natural gas (CNG) from becoming more prevalent in the transportation industry. The ambient energy density of methane, the main component of natural gas, is 0.04MJ L-1. Gasoline offers 32.4MJ L-1 as it is a liquid at ambient conditions [1]. CNG is conventionally stored at 200-300 bar at room temperature yielding mass densities of 160-200 kg/m3. To make natural gas more attractive to consumers and industry, higher densities must be achieved without resorting to such high pressures.

This project seeks to evaluate and improve the storage density of absorbed natural gas (ANG), which use a sand-like bed of metal-organic frameworks (MOF) particles to concentrate the gas at low pressures. As a result, a similar gas density in an ANG tank at 100 bar can be observed as in the CNG tank at 250 bar [1]. MOFs are built with metal and organic chemical building blocks. These frameworks can be chemically synthesized and resemble grains of fine sand [2]. With crystal sizes ranging from microns to millimeters, MOF grains harbor trillions of nanoscale pores that allow for adsorption of gas molecules. Some common MOFs are shown in figure 1.

MOF-74

MOF-5

Cu-BTC

PCN-14

Figure 1: Nanoscale view of four common MOFs. Cu-BTC was studied by Mason et al. and found to be the optimum MOF for methane capture.

METHODS The project consisted of a thorough computational analysis of a tank filling process.

Flow rate into the tank was given by an industrial, natural gas compressor [3]. As the pressure in the tank rose, the flow from the compressor reduced according to Bernoulliâ&#x20AC;&#x2122;s flow equation. The filling process was terminated when the desired pressure in the tank was achieved. The variables recorded during the process were time, mass delivered, tank pressure, and flow rate, all in SI units.

The tank-filling process was first studied in detail without the inclusion of a MOF. This was done to develop an understanding of the mechanics of free-flowing gas into a tank. The equations used in this analysis were Bernoulliâ&#x20AC;&#x2122;s flow through a pipe, and the Peng-Robinson equation of state for non-ideal gases. The specifications for the compressor, which delivered the high-pressure gas, were given by Sauer Compressors USA. Conventionally, volumetric delivery rates are reported by the manufacturer in cubic foot per minute (CFM). Instruments such as flow regulators allow users to adjust the delivery rate to fit their application [3]. The tank was modeled after the average 20-gallon fuel tank found in motor vehicles, modified to accommodate CNG. After a standard tank was studied in detail, an inert, packed bed was inserted. Incorporating MOF structures into the tank was done by designing a fixed, packed bed of particles located at the entrance of the tank.

The Ergun packed bed equation served as the mathematical tool to analyze the effects of the inclusion of a packed bed. The initial bed was designed to consist of various grades of sand. The specifications for sand were given by the Krumbein Phi Scale and the International Scale (ISO) which outlines grain sizes from millimeters to microns [4].

Results given by the Ergun equation could then be extended to fit the behavior of the MOF frameworks in the tank. Cu-BTC was chosen to make up the initial MOF bed due to its high affinity for methane [1].

RESULTS Overall, there was an observable decrease in mass flow rate caused by the packed bed of particles. The bed slowed the flow from the compressor by a degree that was proportional to its influence. For example, a compressor which operates at 206 bars and 3 CFM would take 83.8 seconds to fill a 20 gallon tank from 1 to 200 bar.

The inclusion of a Cu-BTC packed bed, occupying 10% of the tank, increased the fill time to 348.8 seconds. The packed bed added about 14.2 effective liters to the volume of the tank, while only occupying around 3 L itself. Figure 2 is models the tank pressure evolution under isothermal conditions.

10

2.5

Gas Flow Rate vs Time

7

2

1.5

pressure (Pa)

DATA AQUISITION & IMPLEMENTATION We simultaneously solved the Bernoulli equation alongside the Peng-Robinson equation-ofstate using discrete timesteps. With each progressing time step, mass was delivered to the tank, pressure calculated and adjusted, and a new flow rate consequently applied to the next time step.

Various starting flow rates were tested, as well as a myriad of desired tank pressures and sizes. After the free-flow operation had been successfully modeled with sufficient accuracy, inert beds were inserted.

The Ergun equation would apply a reduction in pressured flow from the compressor, resulting in a reduced initial flow rate. Multiple bed arrangements consisting of sand with grain sizes from 625 microns to 1 millimeter in radius were tested. After successfully modeling sand beds, a Cu-BTC MOF bed was tested.

The data which describes the absolute loading of methane onto Cu-BTC was acquired through molecular simulation via the computational software called RASPA. It delivered data at 300K for the volumetric and gravimetric loading that CuBTC allows from 1 to 200 bars of pressure. The isotherm data was recorded, along with the bulk density of the gas at each pressure. These values were used to add the effective volume for gas adsorption because of the inclusion of MOF. Just as a sponge allows water to absorb into its pores, CuBTC would allow gas into its pores.

A MATLAB code was written to make the analysis convenient. Testing with a MATLAB program allowed for quick and easy adjustments in code as well as convenient memory storage into variables.

1 empty tank packed bed tank

0.5

0 0

50

100

150

200

250

300

350

time (s)

Figure 2: This graph visualizes the relationship between pressure and time to fill the CNG tank.

DISCUSSION The variable which has the most effect on fill-time would be the delivery rate of gas from the compressor. The effective volume in the tank also plays a major role in fill-time. As inert bed depths increase, less volume is allotted for gas storage. In the case of MOF beds, bed depths would increase volume for gas storage, however, flow would be significantly reduced due to very small crystal sizes.

Therefore, optimization must be implemented to determine the highest volumetric loading while avoiding excess pressure drop.

Future work would include heat dynamics between the bulk fluid and MOF. A considerable spike in temperature, caused by heat of adsorption into the MOF, would affect the compressibility of methane, and therefore would need compensation by cooling or slower filling. Safety regulations would also require precise cooling and insulation to prevent unwanted combustion. If interest and funding were concentrated on this project, a considerable improvement in the transportation industry would be observed and society would be one step closer to improved energy management.

REFERENCES 1. Mason et al. Evaluating metal-organic frameworks for natural gas storage. Chem.

Sci, 2014, 5, 32-46.

2. Kim, K. et al. High-rate synthesis of Cu-BTC MOF, Chemical Communications Cambridge., Oregon State University.

3. https://www.sauerusa.com/compressed-natural-gas-cng/ 4. W.C. Krumbein & LL Sloss, Stratigraphy and Sedimentation, 2nd edition (Freeman, San Francisco, 1963).

ACKNOWLEDGEMENTS This project was possible with the generous funding and support of PPG Foundation and the University of Pittsburghâ&#x20AC;&#x2122;s Swanson School of Engineering.

IMPROVING FABRICATION OF TOPOGRAPHICALLY ACTUATING VASCULAR GRAFTS Nicholas P. Strauch, Ya Gao, and Sachin S. Velankar Department of Chemical Engineering University of Pittsburgh, PA, USA Email: nps19@pitt.edu INTRODUCTION Vascular bypass is a surgical procedure in which a vascular graft is connected to a patient’s vasculature, replacing damaged or clogged vessels. In small diameter situations (<6 mm), human tissue is used almost exclusively, due to rapidly deteriorating patency in synthetic prostheses. Loss of patency is caused by thrombus accumulation on the inner surface of the graft, due to platelets adhering to the foreign material [1].

To combat this issue, a method has been developed at the University of Pittsburgh utilizing topographic surface actuation to continuously remove foulants from a surface. A bilayer tube is created, composed of a soft outer layer and a stiff inner layer. A strain mismatch is generated in these materials which forces the inner surface to buckle at low internal pressure, forming a wavy surface [2]. When pressure is increased, the tube expands and the inner surface flattens. The mechanism is driven by cyclical internal pressure variation, conveniently provided by the cardiac cycle. The actuation between a wrinkled and flat surface induces strain on platelets causing them to detach and re-enter the bulk fluid.

While a preliminary in-vivo porcine experiment has demonstrated the effectiveness of this mechanism, issues remain in graft fabrication. Materials used in prior studies were not medical implant grade.

Additionally, silicones in general are not thromboresistant. Sample-to-sample reproducibility was also poor due to a complicated fabrication procedure with large inherent variation. The goal of the work presented here was to improve the manufacturing methods and materials, to take the graft a step closer to clinical use. The desired graft would expand 10% between 80 and 120 mmHg and have wrinkles of 50-100 μm. Prior experiments suggest that these parameters are suitable for significant decrease in thrombus formation.

ORIGINAL PROCEDURES AND RESULTS The grafts were originally made by the following procedure. A soft silicone (Silicone, Inc. GI 245) was mixed and dip coated twice onto a 3 mm diameter acrylic rod to get an approximately 2 mm thick layer of silicone. The same was done for a stiffer silicone (Xiameter® RTV-4136M) on a 6 mm acrylic rod, with the addition of 40% by weight of hexane to produce a much thinner layer. Both materials were left to cure. Then, the soft silicone was removed from the rod, resulting in a tube. To create a bilayer, this tube was stretched over the 6mm rod and thin silicone film, using additional uncured soft silicone to bond the two layers. The graft was left to cure at room temperature, and the bilayer was removed from the 6 mm rod. The result was a bilayer graft with wrinkles. This graft did not have the desired stiffness, however, so it was then dip coated twice in another stiff silicone (Silicones, Inc. GI 380).

The grafts produced by the original procedure had the following problems. The soft tube geometry was not uniform. There was a gradient of thickness due to gravity, and the cross section was not perfectly circular. Wrinkle wavelengths less than about 200 µm were difficult to realize and varied significantly from sample to sample. The outer stiffening coating of GI 380 was highly non-uniform and none of the materials used were medical grade.

NEW PROCEDURE AND RESULTS The following improved procedure using medical materials was developed to improve graft reproducibility and bring the project closer to a clinical product. The wrinkling mechanism exploited here requires bonding a thin stiff luminal layer to a softer tubular wall layer. Two silicones were chosen.

Silastic® MDX4-4210 Medical Implant Grade Elastomer (MDX) was selected for its high stiffness.

An implant grade silicone of the desired softness was not available. Hence, DOW Corning® MG7-9900 Soft Skin Adhesive (MG) was selected. Although

MG was difficult to handle due to its sticky texture, mixtures of MG and MDX provided the desired modulus to serve as the tubular wall material.

Multiple ratios of MDX and MG were tested by creating tubes of them and inflating them with water at static pressures of 80 and 120mmHg. It was found that 1:6 weight ratio of MDX to MG produced tubes that expanded adequately in the desired pressure range. Stress strain curves of a selection of the mixtures were generated, as seen in Figure 1. The difference in slopes between MDX and 1MDX:6MG indicates suitable mismatch in elasticity.

unrolling it on the 6mm rod was used, which minimized any possible damage of shearing the film.

Then, the bilayer was left to cure in 70 C for 2 hours before being removed from the rod. Figure 2C shows this process resulting in a tube that wrinkles and flattens with a decrease or increase in pressure.

Figure 2: A. Dip coating schematic for thin film. B. Soft tube molding schematic and resultant tube. C. Bilayer graft composition process. D. 4x image of graft cross section.

Figure 1: Experimental stress-strain curves of MDX/MG samples from tensile testing.

To create the thin film of MDX, the dip coating procedure described above was used, as sketched in Figure 2A. MDX thickness was controlled by addition of hexane as a solvent. A 1:2 weight ratio of MDX and hexane produced desirable thickness around 15 to 20 μm consistently. This was left to cure while spinning horizontally to maintain uniformity.

A molding approach was used to create the MDX/MG tube at 1:6 ratio, shown in Figure 2B. The molded tubes had excellent uniform geometry, controlled by the 5 mm diameter shell and 3 mm rod.

This was left to cure at 70 C for at least 3 hours, accelerating the curing process without affecting subsequent adhesion to the thin film. The soft tube was easily slid off the 3 mm rod (unlike the industrial silicones used previously). The result of this process was a high quality cylinder, apart from some “flash” produced at the seams of the mold. Since this defect was external of the tube, it did not significantly affect the bilayer wrinkling mechanism.

Using additional 1:6 MDX/MG mixture as glue, the tube was adhered to the thin film on the 6mm rod. A technique of rolling the tube into a donut shape and

The overall tubes created using a 15-20μm MDX film and a 1:6 MDX/MG tube (3mm ID, 5mm OD), produced a graft with wrinkles at about 60 μm wavelength, shown in Figure 2D. In static pressure experiments, the tube was found to expand only 3.9% between 80 and 115 mmHg. However, between 80 and 130 mmHg expansion was 10.9%.

DISCUSSION The improvements made with the new materials and procedures have allowed for more control of graft fabrication. It is believed these materials could be approved for this application, but not for blood contact, so further steps will be taken to coat the inner graft surface with PTFE. Additionally, it is unknown how these materials may deteriorate over time. This project was successful in creating wavelength and tube expansion very close to the desired parameters. With slight adjustment to the amount of hexane used in dip coating and the ratio of the MDX/MG mixture, these goals should be met.

REFERENCES 1. Desai et al. J CardioThorac Surg Euro 40, 394, 2011.

2. Pocivavsek et al. Science 320, 912-916, 2008.

ACKNOWLEDGEMENTS Thanks to the University of Pittsburgh Center for Medical Innovation and Swanson School of Engineering, as well as J. Andrew Holmes for making this project possible.

DEVELOPING CEMENTITIOUS MATERIALS FOR ANALOGUE EXPERIMENTS IN HYDRAULIC FRACTURING Taylor DaCanal Department of Civil & Environmental Engineering University of Pittsburgh, PA, USA, Email: trd35@pitt.edu INTRODUCTION One of the challenges of hydraulic fracturing is the containment of the fracture to grow in the desired formation(s) [1]. Vertical containment is controlled largely by two features in layered rock; 1) a weak interfacial shear strength of the layers and 2) a compressional increase in the minimum horizonta l stress in the bounding layer. The variations is stress can result from the different properties that each rock layers have [2].

Mechanically testing different combinations of rock layers will allow a better understanding of the interaction between layers. To allow for precise tuning of specific parameters of the rock layers mechanically analogous materials made of Portland cement, aggregate and other additives were created for the testing to mimicked sandstone and shale.

The analogous sandstone mixâ&#x20AC;&#x2122;s characteristics required a high stiffness and a high porosity, while the shale mix required a low porosity and low stiffness. Controlling both porosity and stiffness in concrete mixtures is well documented. However, the challenge was altering both parameters at the same time in a manner counter to typical correlations.

METHODS A mix matrix, as shown in Table 1, was created to examine what mix combinations would be tested.

The water to cement ratio (W:C) and sand to cement ratio (S:C) were two parameters changed in the mixes. To obtain a stiffness a lower sand to cement ratio was used so that more cement was in the mix.

High water to cement ratios were used in mixes needing high porosity. An air entraining admixture, SIKA 360, was added to the imitation sandstone mixture to increase porosity while the mix contained high amounts of cement to maintain a high stiffness.

The air entrainer allowed for small bubbles to from during the curing process creating small capillar ies for a more porous material.

Each mix was mixed according to ASTM C 305-14, Standard practice for Mechanical Mixing of Hydraulic Cement Pastes and Mortars of Plastic Consistence.

The mixes were cast in custom made molds with a length of 5 inches and radius of 1 inch. Mixes cured in a water bath for 7 days to gain strength before testing.

Water to Cement Ratio vs Sand to Cement 0.3 0.4 0.5 0.6 1 X X 1.5 2 X X X X 2.5 X X X X 3 X X X 3.5 X

Ratio 0.7 X X

Table 1-X-Sandstone Mixture (with air entrainer), X-Shale Mixture (without air entrainer) DATA ANALYSIS The wave velocity, volume, saturated weight, and dry weight were measured for each specimen. From these, estimates were calculated for the porosity of each specimen. The wave velocity was obtained using ultrasonic testing, as seen in Figure 1. Porosity was calculated by the determination of the volume of voids (đ?&#x2018;&#x2030;đ?&#x2018;Ł ) divided by the total volume (V) of the đ?&#x2018;&#x2030; specimen, đ?&#x2018;&#x2DC; = đ?&#x2018;Ł . đ?&#x2018;&#x2030;

RESULTS Figure 2 shows the wave speed and porosity of the analogue sandstone and shale mixes. Mixes 1 and 2 are the mixes that are closest to desired characteristics whereby the analogue sandstone is high porosity and high stiffness while the analogue shale is low porosity and low stiffness. Mix 1 is the best analogue sandstone mix. It has a water to cement

ratio of 0.4 and a sand to cement ratio of 2. This mix also includes six percent air entrainer. Mix 2, the analogue shale mix, has a water to cement ratio of 0.3 and a sand to cement ratio of 3. This mix has no air entrainer.

larger water to cement ratios could be used. The larger water to cement ratios would be helpful in the imitations sandstone mixes because with increased water content there is an increase in porosity. The highest sand the cement ratio of 3.5 was also due to a limitation of the molds. A higher sand to cement ratio was too weak to allow specimen to be removed from the molds without incurring damage.

Different materials can also be considered to obtain desired results. A hydrostone material (plaster) can be used for the sand stone mixture. From previous research a common Young’s modulus for hydrostone is 8 GPa [3]. Using this material as the analogue sandstone mix would give a Young’s modulus ratio of about 2.

Figure 1-Ultrasonic testing specimen and transducer configuration The estimated young modulus ratio of these two mixes is obtained from the wavespeed and density data and is found to be 1.24. The estimated porosity ratio is 1.22. These ratios are lower than the targeted ratios; a larger contrast is needed. The desire was for the porosity to differ by a factor of 5 and the stiffness by a factor of 10.

Figure 2-Wave Speed vs Porosity DISCUSSION The ranges of the water to cement ratio as well as the sand the cement ratios were determined by looking at previous research, but they were also limited by the style of the molds used. The maximum water to cement ratio was 0.7; a water to cement ratio any larger could not be used in the molds because the mixes would be too watery for the molds to hold. If a mold that did not have seams that could leak a

For the imitation shale mixture a suggested material is cement paste. The cement paste would be low in stiffness because of the absence of larger aggregate and it would be low in porosity because of the small cement particles filling all voids. Past research has found the Young’s modulus of cement paste to be around 2.3 GPa [4]. This is significantly lower than the sandstone mixes tested in this research, allowing for a Young’s modulus ratio of around 3 if used in conjunction with hydrostone.

Continued research with new materials is thus needed to obtain the desired material properties. It is recommended to begin this exploration using hydrostone and cement paste materials.

REFERENCES 1. Nordgren. Propagation of a Vertical Hydraulic Fracture 12, 306-314, 1972.

2. Daneshy et al. Factors Controlling the Vertical Growth of Hydraulic Fractures. 2009 3.Dr. Andrew Bungers Masters Thesis 4. Kaxiras et al. Modelling and Measurement of Elastic Properties of Hydrating Cement Paste, 1128, 2010.

ACKNOWLEDGEMENTS This summer research fellowship award was funded by the University of Pittsburgh’s Swanson School of Engineering and the Office of the Provost.

Additional funding was provided by the Univers ity of Pittsburgh Department of Civil and Environmental Engineering.

TIME DEPENDENT HYDRAULIC FRACTURE INITIATION IN LIMESTONE AND SHALE Qihang Ou, Guanyi Lu and Andrew P. Bunger Department of Civil & Environmental Engineering University of Pittsburgh, PA, USA Email: qio2@pitt.edu INTRODUCTION The technology of hydraulic fracturing is widely used to improve the productivity of the natural gas and oil from shale and other petroleum reservoirs. The process involves injection of high-pressure fluid into wellbores to create cracks within the rocks for the purpose of providing flow pathways and thereby stimulating production of natural gas or oil. This method is vital to the success of the petroleum industry (e.g. Economides and Nolte 2000).

One important role of hydraulic fracture modeling is to predict hydraulic fracture initiation, that is, the pressure required to be applied within the wellbore to overcome the strength of the rock and the in-situ confining stresses in order to start the growth of a hydraulic fracture. In the classical models of hydraulic fracture initiation (so-called â&#x20AC;&#x153;breakdown modelsâ&#x20AC;?), the initiation is assumed to occur if and only if the near wellbore tensile stress induced by fluid pressure reaches the tensile strength of the rock formation. However, a central question remains unclear: If the pressure-induced tensile stress is insufficient to cause the instantaneous breakdown, can the hydraulic fracture still initiate in a delayed manner due to continuous pressurization after some time period? This problem has been argued to be one of the most important questions that can lead to significant increase in productivity, especially in multi-stage hydraulic fracturing treatments (Q. Lu et al. 2017).

METHODS A device with a core drilling bit was constructed such to drill a hole at the center of limestone samples. After drilling, a 3/8-inch stainless steel tube with two small holes was inserted into the limestone and both sides of the hole on the specimen were glued. We did both confined and unconfined hydraulic fracture tests, with the confinement provided by a 3-axis loading frame (Figure 1 a). A small pump was used to pressurize fluid (water) in an open section of a wellbore drilled through the center of the specimen. A constant pressure that was lower than the breakdown pressure was maintained, and the time to initiation was observed. After 5-10 experiments using different pressures the relationship between time to initiation and wellbore pressure was plotted.

For shale, we performed the same procedure with only confined tests in a loading frame to simulate the stress environment occurring in reservoir formations.

DATA PROCESSING The data were collected by software on a computer.

We collected both applied fluid pressure and the time to hydraulic fracture initiation. Then we plotted the graph of pressure versus time for limestone tests for both confined tests and unconfined tests, and for the confined test in shale.

Figure 1: a.Load frame for confined test. b, Fracture on limestone

RESULTS For the limestone samples we performed seven unconfined tests. The wellbore fluid pressures vary from 1857 to 2566 psi. For the pressure at 1857 psi, the delayed time is 364 seconds, and for the higher pressure, the delayed time becomes lower. There is a negative exponential relationship between these two variables (Figure 2). Note that two of the tests failed. One failed because the glue was not tight enough and the water leaked from the glue at the hole. In the second failure, the specimen failed at only 1600 psi, and the reasons are unclear. Also we note different fracture geometries for higher and lower pressure experiments. For the test at 2566 psi, the fracture is absolutely obvious and the direction is along the vertical axis (Figure 1b), which is an axial fracture. However, for smaller pressures, the cracks on the surface are usually small and difficult observe.

For the confined limestone specimens, we performed three successful tests. The pressures are varied from 2605 to 3004 psi. The relationship between pressure applied and delayed time is similar to the unconfined test.

Furthermore, we found that under confined conditions, the breakdown pressure for limestone is relatively higher than that of unconfined test. We also observe that for these confined tests, the axial fracture is not clear. Note also that two experiments failed. In the first failure a pressure was applied of 2431 psi, and the specimen was not broken after 5349 seconds; we had to then stop the test because the pump ran out of fluid. The second failure is similar, in which we applied a pressure of 2540 psi, and no breakdown was observed in the practically attainable timeframe. We also found that the instantaneous breakdown pressure of the limestone should be around 3244 psi under confined condition.

For the shale test, the results are scattered because of the high-variability of shale specimens. Under confinement, one specimen broke at 1600 psi. Another shale specimen could not be broken even though we applied the highest pressure that can be reached by the pump, 3321 psi.

Because it could not be broken after more than 2067 seconds, we had to stop the test. We then removed the confinement and obtained an unconfined instantaneous breakdown pressure of 2591 psi. These three experiments lead to an observation that shale specimens are highly variable, leading to scattered results. We also observe transverse fractures in the shale cases, in contrast to the dominantly axial fractures in the limestone cases.

We conclude that for limestone, the higher the pressure we applied on the specimen, the faster the hydraulic fracture initiation/breakdown occurred.

Under confinement a similar qualitative behavior is observed, but larger values of the confining stress are required to generate initiation for a given initiation time. For the shale, the relationship between delayed time and applied pressure should be similar, but a trend was not discernable because of wide-variability of the shale samples.

REFERENCES [1] Nolte, K.G.(2000). Reservoir stimulation (Vol.18).

M.J.Economides(Ed.). New York: Wiley.

[2] Lu Q, Lu G, Swarm G, Winner R, Aidaguloy G, Bunger AP. Impact of fluid acidity on the TimeDependent Initiation of Hydraulic Fractures in Carbonate Rocks. 51st US Rock Mechanics Symposium. San Francisco CA. 25-28 June 21017, ARMA 17-0200.

[3] Lu G, Uwaifo E, Ames BC, Ufondu A, Bunger AP, Prioul R, Aidagulov G, 2015. Experimental Demonstration of delayed Initiation of Hydraulic Fractures below the Breakdown Pressure in Granite.Proceedings 49th US Rock Mechanics Symposium, San Francisco, CA, USA, 28 June-1July 2015. Paper ARMA 15-190.

ACKNOWLEDGEMENTS This summer research fellowship award was funded by the University of Pittsburghâ&#x20AC;&#x2122;s Swanson School of Engineering and the Office of the Provost. Additional funding was provided by the University of Pittsburgh Department of Civil and Environmental Engineering.

DISCUSSION

Figure 2: Experimental data for unconfined limestone is shown in blue, while confined tests are shown in red.

BIODIESEL PRODUCTION FROM WASTEWATER MICROORGANISMS: EFFECT OF BIOSOLIDS DRYING METHODS Larissa Gaul, Christina Rogers, Daniel Cha (faculty advisor) Department of Civil Engineering University of Delaware, DE, USA Email: clr76@pitt.edu, Web: http://www.ce.udel.edu/directories/profiles.html?cha INTRODUCTION Wastewater treatment plants use bacteria in an aeration basin to remove organic pollutants in wastewater. After separation by the sedimentation phase, settled bacteria are recycled back to the aeration basin. However, a portion of these recycled microorganisms are discarded as wasted biosolids [1]. Annually, the municipal wastewater treatment facilities in the US produce millions of tons of this waste biosolids that must be safely disposed of [2].

However, lipids can be extracted from the biosolids via the transesterification process to produce biodiesel. In the transesterification reaction, the phospholipids in cell membranes of sludge microorganisms react with an alcohol, such as methanol, and a catalyst, such as sulfuric acid. It produces fatty acid methyl esters, which are the building blocks of biodiesel. The content of the biosolid waste varies greatly depending on how high the treatment method used is, and what, if any, chemicals were used [2]. This opened the possibility of biodiesel yield being related to the organic makeup of the sample tested, rather than the drying methods used leading up to testing. The goal of this experiment, other than demonstrating the process, is to determine whether less intense drying methods will result in a higher yield of biodiesel, and if sample makeup has a large influence in biodiesel yield.

METHODS The study consisted of experiments conducted on three different samples retrieved from Elkton Wastewater Treatment Facility, a local wastewater treatment facility on different dates, either dried thermally on site or retrieved as an activated sludge sample.

For the samples retrieved already thermally dried by the plant, there was nothing that needed to be done except the transesterification process itself. This process begins weighing between 4-5 grams of

dried sludge and placing it into a 250 mL ball flask.

25 mL of hexane is then added, along with 53 mL of a solution consisting of 5% sulfuric acid and 95% methanol. A magnetic stir rod is placed in the ball flask, and the flask is attached to a cold water condenser. Below the condenser, a large beaker with 400-500 mL water is heated to 80-100 째C. Once the water reaches the desired temperature range, the ball flask attached to the cold water condenser is submerged in the water. A magnetic field is turned on to active stirring in the flask, and water supply is turned on to the cold water condenser. The mixture is heated under these conditions for two hours, after which time the mixture should be allowed to cool for ten minutes.

The mixture is then separated into three different centrifuge vials, and 15 mL of hexane is added to each vial. The vials are then centrifuged for 3 minutes at 3000 rpm. The upper layer of hexane is removed and placed in a separatory flask, and this process is repeated two more times. Ten mL of K 2 CO 3 is added to the separatory flask, which is then mixed and left to settle. The bottom layer is removed and the top layer should be put into a clean ball flask. This is put in a rotovap on 60 째C and 30 rpm for 20 minutes, leaving behind a dark layer of oil.

If the sample was received as fresh waste activated sludge from the plant, there are multiple drying methods that can be utilized and were experimented with in this research.

For both 60 째C and 100 째C oven drying, the sludge is put into centrifuge vials and centrifuged for 10 minutes at 4000 rpm. The water is then drained from the vial, and the remaining sludge is placed onto an aluminum foil tray. The sludge is then placed in the desired oven overnight, and ground using a mortar and pestle before transesterification can begin.

For membrane drying, setup is a bit more complicated.

There are two cylindrical compartments separated by a hydrophobic membrane layer. The sludge is placed in the bottom compartment, and a constant flow of ambient air is supplied to the top compartment at a rate of 10-20 L/min for 24 hours. It was found that the sludge wouldn’t dry in this time slot, so the sample was left for 3-5 days and the air flow was always kept around 20 L/min. Upon complete drying, remove the dried sludge from the bottom compartment and grind in mortar and pestle before using in transesterification.

DATA PROCESSING The yield of oil was recorded along with the initial mass of dried sludge used. COD analysis was performed on many samples, and fuel property calculations were done on those which had COD done as well.

RESULTS Sample(g) 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00

Yield (g) 0.15 0.12 0.23 0.15 0.12 0.17 0.10 0.10 Mean

% Yield 3.00% 2.40% 4.60% 3.00% 2.40% 3.40% 2.00% 2.00% 2.85%

Sample (g) 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00

Yield (g) 0.14 0.28 0.26 0.29 0.32 0.11 0.31 0.26 0.30 Mean

% Yield 2.80% 5.60% 5.20% 5.80% 6.40% 2.20% 6.20% 5.20% 6.00% 5.04%

The original samples tested, which were thermally dried by the plant, showed an average yield of 2.85% (left table). The second sample retrieved of thermally dried sludge showed a yield of 5.04% (right table).

Sample (g) 5.00 4.46 5.00 4.48 5.00 5.00

Yield (g) 0.27 0.23 0.50 0.24 0.23 0.21 Mean

% Yield 5.40% 5.16% 10.00% 5.36% 4.60% 4.20% 5.79%

Sample (g) 5.00 5.00 4.90 5.00 5.00 5.00

Yield (g) 0.10 0.14 0.21 0.10 0.30 0.50 Mean

% Yield 2.00% 2.80% 4.29% 2.00% 6.00% 10.00% 4.51%

Two samples of waste activated sludge were retrieved from the plant, and they underwent three

different drying methods – membrane drying, 60 °C drying, and 100 °C drying. Only 100 °C drying was performed on both samples, and the results showed an average yield of 5.79% (left table) for the first sample, and 4.5% (right table) for the second sample.

DISCUSSION The discrepancy in the values of average yield for the different samples of thermally dried sludge indicates that perhaps biodiesel yield is possibly more directly correlated to organic makeup than it is to drying method, because in either of these sets, the drying method used was the same, but the average yields varied greatly. When looking at the average yield for the different samples independent of drying methods, the yields are more closely correlated – the first sample yielding about 5.42%, and the second sample yielding about 2.69%. This suggests that possibly organic makeup is more significant in the yield of biodiesel, or perhaps more data needs to be collected to accurately capture the biodiesel yields of any sample. Future studies will investigate the influence of sample makeup, and further test the biodiesel yield of sludge samples to more accurately determine the main influence of biodiesel yield.

REFERENCES 1. “Recycling biosolids from wastewater treatment facilities.” Department of Environmental Conservation, New York State. August 8, 2017. http://www.dec.ny.gov/chemical/97463.html 2. “Biosolids Generation, Use, and Disposal in the United States.” U.S. Environmental Protection Agency. September 1999. Accessed August 8, 2017.

ACKNOWLEDGEMENTS The samples of waste activated sludge were retrieved from the Elkton Wastewater Treatment Plant in Elkton, MD. Thermally dried plant samples and fresh sludge samples were retrieved. Lab access was granted by the University of Delaware Department of Civil and Environmental Engineering, and was overseen by Dr. Daniel Cha. Special thanks to Swanson School of Engineering staff who made this research position possible, Larry J. Shuman, David A. Vorp, Mary BesterfieldSacre, Gerald D. Holder, and Melissa Penkrot.

DETERMINISTIC SPACE NETWORKING AND TIME-TRIGGERED ETHERNET MODELING Joseph R. Kocik, Dr. Alan George NSF Center for High-performance Reconfigurable Computing (CHREC) University of Pittsburgh, PA, USA Email: jrk123@pitt.edu, Web: http://www.chrec.org/ INTRODUCTION Time-Triggered Ethernet (TTE) is a deterministic and fault-tolerant networking technology of prime interest for space computing systems. These traits along with its compatibility with most Ethernet endsystems make TTE appealing. Using TTE on a space mission requires testing and experience with the technology. Studies are underway to create a simulation of a TTE-compliant system to evaluate the capabilities and limitations of TTE for space.

BACKGROUND TTE is an extension of the standard Ethernet protocol outlined in IEEE 802.3 [1], which adds synchronized system time and a predefined periodic schedule, allowing for messages to be sent with constant latency and minimized jitter.

In TTE, three different traffic types exist, including time-triggered (TT), rate-constrained (RC), and best-effort (BE) traffic [2]. TT traffic transmission is predetermined by a schedule and has guaranteed arrival, low latency, and consistent jitter. RC messages are driven by unscheduled events and are allocated a set bandwidth. While arrival is still guaranteed, the possibility of conflicts increases jitter. BE traffic is the same as traditional Ethernet with no guarantees for arrival, latency, or jitter. BE traffic simplistically uses spare bandwidth that RC and TT traffic are not using.

The TTE protocol allows one networking technology to be used for diverse traffic [3]. The determinism of TT traffic allows for safety- or mission-critical messages to be passed while permitting less critical traffic. This unique capability is particularly relevant to space systems where integrated modular avionics (IMA), having individual computing platforms perform diverse tasks, has become increasingly popular.

TTE MODELING Models of a TTE system were created to simulate a hardware testbed. This system consists of two bridges and four end-systems (i.e., nodes).

Figure 1: Two default configurations of a hardware testbed, dual-channel (top) and multihop (bottom).

The hardware testbed, by default, allows two configurations, dual-channel and multihop (Figure 1). The dual-channel configurationâ&#x20AC;&#x2122;s fully replicated connections between end-systems makes it faulttolerant via dual modular redundancy.

Figure 2: VisualSim model to mimic a hardware testbed.

The models (Figure 2) were built using VisualSim, a commercial, discrete-event, systems simulation software tool with a TTE-compliant library. Nodes and traffic-generation blocks were used as endsystems with bridges to connect them together. The models allow dual-channel and multihop configurations. Traffic sources, destinations,

priority level, routing, and throughput can all be adjusted using the configuration tables.

other traffic types were less consistent, but still had standard deviation on the order of microseconds.

RESULTS

In multihop configuration, two bridges are passed as opposed to one in dual-channel, explaining the higher average latency. The increase was most dramatic in TT traffic with the average latency nearly doubling. This outcome indicates that bridges cause the most latency, as TT traffic is effected by system transmission speed and not by other traffic or collisions. The standard deviation was greater in multihop configuration, for all traffic types. This means that routing traffic to avoid having to cross multiple bridges may not just reduce latency, but it also may reduce standard deviation.

Figure 3: Average end-to-end latency in seconds of traffic sent from Node 1 to Node 4 for dual-channel and multihop configuration across different base periods.

The two configurations were both run across a series of logarithmically scaled base periods, with base period determining frequency of periodically scheduled traffic (Figure 3). This approach allowed observation of the system at varied speeds, as well as investigation of optimal periods for the system.

The traffic throughput was set to be 0.5 Mbit/s for two sources of RC traffic (RC1 and RC2) and BE traffic. TT trafficâ&#x20AC;&#x2122;s throughput was scaled to increase when period decreased, to reduce the standard deviation of latency, as TT traffic is dictated by a periodic schedule. The results showed dual-channel had lower average latency and lower standard deviation. Simulations with increased throughput verified that high levels of throughput for RC or TT traffic (exceeding 100 Mbit/s) throttled the BE traffic down to zero message transmissions.

DISCUSSION The TTE model outputs are consistent with the expected performance of a TTE-compliant system, with a low average latency at low standard deviation. The average latencies were low, and TT traffic performed the best with a low base period.

The standard deviation of latency was on the order of nanoseconds for TT traffic, with the expectation of the multihop at a base period of 10-5 seconds which had a standard deviation of 4.305 Âľs. The

CONCLUSIONS AND FUTURE WORK The simulations performed as expected with latency and jitter kept low by the TTE environment. This was done while maintaining the required faulttolerance and determinism. The next steps of this project are to attempt to replicate the results of the models using the TTE Development System, a hardware testbed being provided by the vendor, TTTech. Testing will be conducted to replicate the results observed with the simulation models. This approach will include investigating the differences in both magnitude and standard deviation for latency between dual-channel and multihop configurations. There is also a strong possibility that TTE will be featured in a future space mission now being planned by CHREC with NASA, affording another opportunity to experiment with a hardware realization of TTE. REFERENCES [1] Aerospace Standard SAE AS6802, 2016.

[2] A. Loveless, "On TTEthernet for Integrated FaultTolerant Spacecraft Networks", AIAA SPACE 2015 Conf. and Exposition, Pasadena, California, 2015.

[3] H. Kopetz et al., "The Time-Triggered Ethernet (TTE) design," Eighth IEEE Int. Symp. on Object-Oriented RealTime Distributed Computing (ISORC'05), 2005, pp. 2233.

ACKNOWLEDGEMENTS The authors would like to thank Chris Wilson and all the CHREC students who assisted in this research. The student would also like to acknowledge Dr. George, CHREC members, the Swanson School of Engineering, and the Office of the Provost for funding this research and Mirabilis Design for free use of the VisualSim tool.

LOW LOSS SURFACE PLASMON PROPAGATION AT SINGLE INTERFACE FOR ANISOTROPIC MEDIA (METAMATERIALS) Karl Sewick and Hong Koo Kim Nanoscale Optoelectronics Lab, Department of Electrical and Computer Engineering, University of Pittsburgh, PA, USA Email: kws13@pitt.edu INTRODUCTION Surface plasmons have applications in communications, computing, sensing, and imaging but are plagued by strong attenuation, limiting practical application. In this research, we derived the governing equations for the most fundamental geometry governing the phenomenon and attempted to improve attenuation over the conventional silverair interface case. The focus of this project is to improve the understanding of relevant parameters for metamaterials for use in low loss surface plasmonics.

Raether et al. provided derivations for the fundamental equations describing the silver-air interface [1]. Based on this analysis, Kim and Wuenschell analyzed the same material system but further understood the underlying mechanisms for the high attenuation in the system [2]. From this analysis, the loss in the propagation originates from the power loss in the metal side of the interface. The absorption in the metal is attributed to the imaginary part of the metal’s dielectric constant. Thus brings in our analysis of a new system.

SETUP The geometry used in our analysis consisted of a dielectric SiO2 and a stacked structure of metaldielectric (Ag-SiO2). This stacked structure is 50% Ag- 50% SiO2, allowing for a much lower imaginary dielectric constant compared to Ag.

From our system design, we began establishing electromagnetic equations to explain the waves as well as the dielectric tensor. We treat the y-direction as the propagation direction. From Maxwell’s equations, we came up with the following:

Hz1 = H0 eKx1 x+iKy y Kx2 x+iKy y

Hz2 = H0 e

Ky ⌘0 H0 Kx1 x+iKy y e K0 ✏m,n Ky ⌘0 H0 Kx2 x+iKy y Ex2 = e K0 ✏ D iKx1 ⌘0 H0 Kx1 x+iKy y Ey1 = e K0 ✏m,t iKx2 ⌘0 H0 Kx2 x+iKy y Ey2 = e K0 ✏ D Ex1 =

In these equations, Ky acts as the decay rate in the propagation direction, and Kxi for decay normal to interface. η0 is wave impedance, and H0 is initial magnetic field intensity. With the E-M fields understood, we developed further equations for the Poynting Vector and expressed the decay rates in terms of physical constants.v Ky =

p

r

u u ✏D t ✏

✏m,t ✏D

m,t

✏D

1

✏D ✏m,n

✏m,t 2 K ✏m,t K02 ✏m,n y q Kx2 = Ky2 ✏D K02

Kx1 =

~=E ~ ⇥H ~ S 2 Kx1 ⌘0 2Kx1 x+2iKy y Sx1 = H0 i K0 ✏m,t e x2 ⌘0 Sx2 = H02 i K K 0 ✏D e

Figure 1: System geometry for anisotropic media single interface.

2Kx2 x+2iKty y

K ⌘

Sy1 =

0 H02 K0 ✏ym,n e2Kx1 x+2iKy y

Sy2 =

x2 ⌘0 H02 K K 0 ✏D e

2Kx2 x+2iKy y

Our calculation for the dielectric constant is a simple parallel-series analysis shown below.

✏m,n = f ✏Ag + (1 ✏m,t =

f ✏Ag

f )✏D 1 + 1✏Df

DATA PROCESSING The simulation was run and modeled in Matlab and tested at incident wavelengths of 300, 325, 532, 600, 633, 900, 980, and 1300nm. Our dielectric constant data for SiO2 and Ag was linearly interpolated from Lemarchand and Johnson, respectively. [3][4] RESULTS In agreement with previous analysis, the loss is found to decrease as a function of wavelength for Ag-SiO2based metamaterials. With our analysis, we obtained a longitudinal propagation of 242.9µm at 1300nm, which is much higher than that of the silver-air interface which has a propagation length << 100µm.

REFERENCES 1. Raether et al. Surface Plasmons on Smooth and Rough Surfaces and on Gratings, 1986.

2. Wuenschell, J., Kim, H., Surface Plasmon Dynamics in an isolated metallic nanoslit, 2006.

3. L. Gao, F. Lemarchand, and M. Lequime.

Exploitation of multiple incidences spectrometric measurements for thin film reverse engineering, Opt. Express 20, 15734-15751 (2012) 4. P. B. Johnson and R. W. Christy. Optical Constants of the Noble Metals, Phys. Rev. B 6, 4370-4379 (1972) Table 1: Relevant Wavelengths λ(nm)

ϵSiO2

325

2.23

633

2.17

980

2.15

1300

2.15

Parameters

for

Varying

ACKNOWLEDGEMENTS Work was funded through Swanson School of Engineering, PPG, and Dr. Hong Koo Kim.

ϵAg

ϵm,n

ϵm,t

re(Kx1)m ^-1

re(Kx2)m ^-1

im(Ky)m^1

Prop.

Length

MM Penetration Depth

SiO2 Penetration Depth

Oscillation Wavelength

.009+ 0.498i -18.3 +0.48i -48.5 +0.56i -89.3 +2.08i

2.234+ 2.2256i 4.915+ .0172i 4.51+ .0024i 4.405+ .00253i

1.12+ 1.1171i -8.077+ .2396i -23.17+ .2785i -43.599 +1.04i

6.56E+06

9.27E+06

9.27E+06

54nm

76.22nm

53.94nm

280nm

2.00E+07

5.35E+06

2.73E+04

18.324µm

25nm

93.46nm

403.78nm

2.18E+07

2.03E+06

2.57E+03

194.63µm

22.936nm

246.3nm

652.77nm

2.26E+07

1.11E+06

2.06E+03

242.89µm

22.124nm

450.5nm

875.92nm

DIFFERENTIAL ACTIVATION OF REST-STATE CORTICAL NETWORKS IN FIRSTEPISODE SCHIZOPHRENIA-SPECTRUM PSYCHOSIS Henry Phalen1, Brian Coffman2, Dean Salisbury2, and Ervin SejdiÄ&#x2021;1 Innovative Medical Engineering Developments Laboratory, University of Pittsburgh, Pittsburgh, PA, 2Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburgh, PA Email: henry.phalen@pitt.edu, Web: http://www.imedlab.org/ 1

INTRODUCTION Schizophrenia is a chronic mental disorder that can result in particularly disabling cognitive, physical, and emotional symptoms. While decades of research have resulted in pharmacological and psychosocial treatments for the disease, the exact etiology remains unknown. Understanding differences in cognitive function between individuals with Schizophrenia and those without the disorder could lead to improvements in treatment and diagnosis. In this study, we use a machine-learning clustering technique, non-negative matrix factorization (NMF), to analyze phase-synchrony graphs from Magnetoencephalography (MEG) data. NMF has previously been used to investigate differences between subject groups using functional MRI (fMRI) [1]. We expand use of this technique, both to the investigation of Schizophrenia and to the analysis of MEG data. MEG provides high spatial and temporal resolution, thus enabling precision in signal processing that is not always possible with other imaging modalities.

METHODS Five minutes of rest-state MEG data were collected from 31 individuals with first-episode schizophreniaspectrum psychosis (SCZ) and 22 healthy controls (CON) using a 306-channel Elekta Neuromag Vectorview MEG (Helsinki, Finland). Subjects were instructed to fixate upon a central cross-hair for the duration of the test. Head movement and external noise corrections were made using Elekta MaxMove and Elekta MaxFilter, while eyeblink and heartbeat artifacts were removed using Adaptive Mixture Independent Component Analysis. Preprocessed data were source-resolved to the surface of the cortex, which was estimated from T1-weighted anatomical MRI. Forward and inverse modeling (minimum-norm estimation) were performed, and data from each subject were then morphed into Montreal Neurological Institute standard space.

The first principal component of the signals from 40 Brodmann areas of each hemisphere was used to represent regional activity. These 80 component signals were bandpass filtered into the alpha (8â&#x20AC;&#x201C;12 Hz) frequency band. Synchrony was approximated between the phases of the analytic component signals using single-trial phase-locking values (S-PLVs) calculated for 600ms non-overlapping windows which are six times the length of the mid-band period [2]. These S-PLVs were used to create weighted, undirected synchrony graphs for each window. The graphs were thresholded at the 95th percentile of SPLVs generated from post-processing 200 random Gaussian surrogate signals [2].

NMF, an unsupervised machine-learning technique, determines two matrices that multiply to best approximate the input in a way that provides timebased clustering information [1]. As the synchrony graphs are undirected, all functional relationships can be described in a single matrix by unwrapping and concatenating the upper triangular of each graph.

Factoring this matrix with NMF provides component subgraphs and timeseries corresponding to the relative activation of each subgraph in the input graphs. The number of subgraphs was selected by determining the point of inflection in the derivative of the reconstruction error curve [1].

The energy đ??¸đ??¸đ??¸đ??¸đ??¸đ??¸ and entropy đ??¸đ??¸đ??¸đ??¸đ??¸đ??¸ of the activation timeseries associated with each subgraph were calculated for each subject by đ??¸đ??¸đ??¸đ??¸đ??¸đ??¸ = â&#x2C6;&#x2018;đ??żđ??żđ?&#x2018;&#x203A;đ?&#x2018;&#x203A;=1 đ?&#x2018;&#x2020;đ?&#x2018;&#x2020;đ?&#x2018;&#x203A;đ?&#x2018;&#x203A; 2 and đ??¸đ??¸đ??¸đ??¸đ??¸đ??¸ = â&#x2C6;&#x2018;đ?&#x2018;&#x203A;đ?&#x2018;&#x203A;đ?&#x2018;&#x2013;đ?&#x2018;&#x2013;=1 â&#x2C6;&#x2019;đ?&#x2018;&#x192;đ?&#x2018;&#x192;(đ?&#x2018;Ľđ?&#x2018;Ľđ?&#x2018;&#x2013;đ?&#x2018;&#x2013; ) đ?&#x2018;&#x2122;đ?&#x2018;&#x2122;đ?&#x2018;&#x2122;đ?&#x2018;&#x2122;đ?&#x2018;&#x2122;đ?&#x2018;&#x2122; đ?&#x2018;&#x192;đ?&#x2018;&#x192;(đ?&#x2018;Ľđ?&#x2018;Ľđ?&#x2018;&#x2013;đ?&#x2018;&#x2013; ), where đ??żđ??ż is the length of timeseries đ?&#x2018;&#x2020;đ?&#x2018;&#x2020; and đ?&#x2018;&#x192;đ?&#x2018;&#x192;(đ?&#x2018;Ľđ?&#x2018;Ľ) is a probability function derived from a histogram of the data. The measures were compared between the SCZ and CON groups using the Wilcoxon ranksum test (p<0.05).

RESULTS The optimal number of subgraphs was determined to be 17 via the reconstruction error optimization

method. Without a priori knowledge in the input, many of these subgraphs displayed regional neural clustering. Particularly, individual subgraphs showed clustering indicative of both intra-lobe and between-lobe connections.

Figure 1: Subgraph 14 is one of the four subgraphs generated via NMF that had significant differences in activation between SCZ and CON. This subgraph primarily contains connections from and between the right and left parietal lobes of the brain. At the right, a top and rear view of the network is given considering edges within 33% of maximum value in the connectivity subgraph shown at left.

Four subgraphs exhibited a significant decrease in median energy between the SCZ and CON groups.

These subgraphs consist of networks within and extending from the left temporal and right frontal lobes, as well as networks in between both parietal and frontal lobes. Of these four subgraphs, three showed significant decreases in median entropy while the fourth did not have a significant change.

For brevity, a single subgraph and associated activation measures are given in Figures 1 and 2, respectively.

ACKNOWLEDGEMENTS Partial funding for this research was provided by the Swanson School of Engineering and the Office of the Provost at the University of Pittsburgh

Figure 2: A representative comparison of subgraph activation measures between SCZ and CON is given. Data are from subgraph 14. Median energy and entropy are smaller for SCZ than CON. The p-value associated with a Wilcoxon ranksum test is given beneath each plot.

DISCUSSION The regional clustering of subgraphs formed by NMF is particularly interesting as it suggests the method identifies networks that have some physiological relevance. Similar meaningful clustering has also been observed using NMF with fMRI data [1]. Combined, these results indicate that this technique holds promise for improving the understanding of communication network activity in the brain without the use of a priori templates.

Subgraph energy represents the overall quantity of communication occurring in a subnetwork whereas entropy indicates how much network activation is changing. Significant decreases in both activity measures were observed in several alpha-band subgraphs in this study. As alpha-band signals are thought to contribute to long-range inhibition of cortical function [3], the decreased activity may be indicative of a decrease in inhibition consistent with pathologies of Schizophrenia [4]. The regional clustering of these subgraphs also allows for further focused study into select regions of the brain with the goal to isolate the root cause of the symptoms associated with Schizophrenia.

Analysis of phase-synchrony networks from MEG data using NMF shows promise for identifying differences in the cortical communication of individuals with Schizophrenia and those without the disorder. Additionally, differences in subgraph activation may be used to support clinical hypotheses about Schizophrenia, including that the disorder may be associated with decreases in long-range alphaband inhibition. We plan to further improve our analysis by investigating correlations between subject clinical attributes and subgraph activity.

KINETICS OF SELF-FOLDING SHAPE-MEMORY POLYMERS ACTIVATED BY LOCAL RESISTIVE HEATING Evan M. Poska*, Moataz Elsisy, Mostafa Bedewy** Department of Industrial Engineering, Swanson School of Engineering University of Pittsburgh, PA, USA Email: *emp90@pitt.edu, **mbedewy@pitt.edu, Web: http://nanoproductlab.org/ INTRODUCTION A temperature gradient across the thickness of a prestrained polystyrene, which is a shape memory polymer (SMP), causes the hotter side to shrink more than the cooler side. The heat induces self-folding, when it is focused along a line. This is the basic idea behind origami engineering of SMPs: creating a functional 3D structure from a 2D sheet. Local and uniform heating methods already explored for that purpose include lasers [1], conventional oven heating [2], microwaves [3], intense light [4], and resistive heating [5]. The purpose of this project is to characterize the local heating effects on prestrained polystyrene using resistive heating. This can be done by applying a current through resistive wire in contact with the polystyrene (PS). Results show that electric current, wire characteristics, and use of surface adhesive material can effectively control fold time and angle. This will enable the creation of complex 3D shapes based on bidirectional folding.

Hence, such approach of creating compliant mechanisms is a promising manufacturing route for light weight structures.

METHODS DC Power Supply (B&K Precision) with single output and range of 0 to 18 V was used, which allows current controlled mode. The following resistive heating wire was used: Omega NCRR-23-100 .0063” x .0625” 1.38 Ω/ft); Kanthal A-1 (Temco .5x.1mm 9.2 Ω/ft @ 68° F), and the temperaturecurrent calibration is shown in Table 1. White polystyrene (Sibe Automation .010” thick high impact) was used for all of the pre-strained polystyrene (PSPS) tests. Plastruct .010” styrene was used for all of the non-pre-strained (NPS) control tests. All samples were cut to 10x20 mm. Doublesided Kapton (polyimide) is used in some experiments.

DATA PROCESSING Angles were graphed with respect to time using MS Excel at intervals of 1-10 seconds, depending on the speed of fold. The angles were recorded manually by reviewing the video of each trial.

RESULTS For the experimental setup, shown in Figure 1, a glass slide was used as a platform to which roughly 8 mm of the PS was taped such that 12 mm hung off the end. To ensure uniform and repeatable pressure on the PS, the resistive ribbon was securely clamped with alligator clips and allowed time to reach peak temperature before contact with the PS. Experiments were recorded at either 720p or 1080p, and 30fps or 60fps with a protractor behind the folding to measure the angle with time. A microscope video camera focused on the hinge during folding, recorded the heat effect on the material with time at 7fps. Initial tests using resistive round heating wires were not as effective as the flat ribbon heated on the edge or flat side. The best results came from the ribbon edge of NCRR-23-100 Ni80/Cr20, which is what will be reported on in this paper, as shown in figure 2.

Compared to bare PS with no tape, PS with tape on one side melted/shrunk less on the sides of the hinge.

Table 1: Resistive wire temperature at each current Current (A) Temp (°C)

2.20 89.75

2.40 101.15

2.60 113.05

2.80 124.25

3.00 137.45

Fig. 1. Experimental setup

DISCUSSION The large times required for folding at low currents may not be applicable in a real manufacturing setting, or may require a force on the folding side during heating to hasten a precise fold. This assistive method may be valuable for any current, given the variability in fold times. Our results indicate that compressive forces between the resistive wire and polymer greatly influence fold time, angle, and melting/shrinking at the hinge. Excessive force

causes the resistive wire to embed itself in the polymer. Uneven—i.e. misalignment between polymer and resistive wire—force usually prevents any folding at all. The bi-material effect of polyimide tape on polymer is one of the more interesting results, because it enables bi-directional folding using a single wire (Figure 2. g). We propose that the opposing effects of thermal shrinkage of the polymer along with the expansion of the tape induce constantly fold with the tape on the outside.

Fig. 2 (a) Schematic of folding with tape on the heated side. (b, c) Results of PSPS (a) and NPS (b) folding angle with time for the configuration shown in (a). (d) Schematic of folding with no tape. (e, f) Results of PSPS (e) and NPS (f) folding angle with time for the configuration shown in (d). (g) Bi-directional folding of one sample heated on the tape and bare sides of PSPS.

Future work may include larger samples with complex arrangements of geometrically and physically different wires for sequential folding with different angles. This could be combined with the heat lamp and laser methods, for inner folds that the main stimulus can’t reach. Springs may also be used to standardize the force between the wire and PS. REFERENCES [1] Y. Liu et al., J. Appl. Phys. 115, (2014).

[2] M. T. Tolley et al., Smart Mater. Struct. 23, 94006 (2014).

[3] D. Davis et al., RSC Adv. 5, 89254 (2015).

[4] [5]

Y. Liu et al., Soft Matter 8, 1764 (2012).

S. M. Felton et al., Soft Matter 9, 7688 (2013).

ACKNOWLEDGEMENTS Setup was funded by Dr. Bedewy’s start-up fund from the department of Industrial Engineering at Pitt.

E. Poska was supported by the PPG Foundation through the SSoE undergraduate research program.

Biocompatibility and Functionality Assessment of a Novel Nitinol Tongue Prosthetic Device to Treat Dysphagia James Kern, Yanfei Chen, and Youngjae Chun Biomanufactoring and Vascular Device Laboratory University of Pittsburgh, PA, USA Email: JamesKern@pitt.edu

Dysphagia is a medical issue wherein the patient has difficulty or pain while swallowing (odynophagia) [1]. Within the United States alone up to 16.5 million senior citizens may require treatment for dysphagia [2]. Current treatments for oropharyngeal dysphagia involve use of a videofluoroscopic swallow study (VFSS) followed by rehabilitation techniques to develop a safer swallowing method and there is no implantable medical device currently available. Therefore, we are working to develop a mechanical prosthetic tongue which can be placed within the mouth similar to a denture to improve the swallowing motion, specifically in the oropharyngeal phase. This study assesses the biocompatibility properties of several silicone polymers that could serve to cover the nitinol matrix of the tongue prosthetic device.

Additionally, an in vitro custom swallowing test model analyzes the mechanical properties of the tongue prosthetic prototypes.

Materials and Methods Biocompatibility testing focused on the cell viability and proliferation of human adult keratinocyte cells on platinum silicon, polydimethylsiloxane (PDMS), and carbon silicone to assess cytotoxicity of the polymers.

Two sets of 25cm2 samples of each polymer were plated separately with cells for 24, 48, and 72 hours respectively. To assess cell proliferation scanning electron microscope (SEM) images were taken of one set of samples. Three 255mm2 regions on each sample were imaged with the number of cells in each images manually counted

and averaged to approximate the number of cells per sample. A fluorescence stain was used on the second set of samples. Three images were taken of each sample with three representative regions on each image selected for intensity measurements using ImageJ software. ImageJ measurements were exported into excel to compute the corrected total cell fluorescence (CTCF) within each region. The swallowing test model was designed using PDMS for soft tissue and 3-d printed mandible and maxilla. It utilizes a mechanical lever system to simulate a chewing motion. A pressure sensor (IOPI Medical) is attached to the palate to measure the force exerted by the tongue prosthetic during the simulated chewing motion.

Results and Discussion Figure 1 displays the CTCF of each polymer tested over a period of 72 hours. To eliminate discrepancies between sizes of the cells analyzed, CTCF per unit area

Introduction

250.00 200.00 150.00 100.00 50.00 0.00

24 Hours 48 Hours 72 Hours

Figure 1: Contains 24, 48, and 72 hour CTCF data of the three polymers tested with standard error bars

the CTCF per unit area is reported.

Figure 2 contains representative SEM images of each polymer after at least 24 hours of culturing.

SEM results followed a similar trend of increased

cell proliferation over extended time periods.

PDMS contained approximately 50% more cells then both platinum silicon and carbon silicon at each time period. Additionally, both Carbon Silicon and PDMS experienced a sharp increase in cell count after 48 hours.

representative regions of each sample selected for analysis or the short time period for cell growth and proliferation.

Acknowledgements Central Research Development Fund from the University of Pittsburgh.

References [1] "Dysphagia." National Institutes of Health.

U.S. Department of Health and Human Services, 15 Nov. 2016.

[2] ClavĂŠ, Pere, et al. "Diagnosis and Management of Oropharyngeal Dysphagia and its Nutritional and Respiratory Complications in the Elderly." Gastroenterology Research and Practice, vol. 2011, 2011, pp. 1-13.

Figure 2: Representative images of PDMS (top), Platinum Silicon (Center), and Carbon Silicon (Bottom).

Conclusions These findings indicate that all three polymers of interest provide an adaquete environment for cell growth and development. SEM results indicate that cell proliferation increased over time with CTCF results indicating cell viability remained high. Based on the large increase of cell proliferation after 48 hours future studies can extend this experiement for a longer duration to see if the rapid cell proliferation continues. Errors in the data could be attributed to poorly

SILICON SOLAR CELL 92.4% SOLAR SPECTRUM ABSORPTION ACHIEVED THROUGH NANOTEXTURING AND THIN FILM ETCHING Danielle Kline Laboratory for Advanced Materials at Pittsburgh, Department of Industrial Engineering University of Pittsburgh, PA, USA Email: drk43@pitt.edu, Web: http://www.pitt.edu/~pleu/Research/ INTRODUCTION Solar cells represent a highly promising domain in advancing renewable energy, but despite an everexpanding solar energy market, efficiency and cost advancements must still be made in order to make solar a truly competitive alternative. One such means of achieving those goals is to use thinner silicon to both increase light trapping effects and decrease material costs. Bulk silicon can be etched down via wet chemical etching to achieve thicknesses as low as 5 microns, which has been achieved here in our lab. Known as ultrathin silicon, the thinned-down wafer boasts desirable properties such as flexibility. A common etchant used is potassium hydroxide, or KOH. By adjusting the etchant bath temperature and concentration, the etch rate of the following reaction can vary immensely: Si + 2OH- + H 2 O→SiO 3 2- + 2H 2 [1] Another way to achieve lower cost and enhanced light trapping is to texture the silicon surface itself.

Black silicon, or bSi, is an effect caused by the nanoscale interaction of a passivation agent and an etchant on a silicon substrate. The resulting surface appears uniformly black due to the light scattering effects of the grass-like columnar nanostructures, and reflection values as low as around 2% have been reported here in our lab. Deep reactive ion etching (DRIE) is a steadfast means of producing black silicon, alternating SF 6 and O 2 plasmas for etching and C 4 F 8 plasma for passivation: O 2 + SF 6 → O* + SF 5 *(or SF 4 *) + F* [2] Variables such as gas flow rate, power, and pressure can be altered to fine tune structure geometries and maximize substrate absorption.

Both methods propose promising solutions to cut down on optical losses and manufacturing costs.

Therefore, by thinning down a standard thickness

black silicon wafer, we were able to produce a sample with 92.4% absorption.

METHODS The deep reactive ion etching was performed on an STS ASPECT Cluster Reactive Ion Etching system at Carnegie Mellon University. A 500 micron <100> SSP c-Si wafer was cleaned with acetone, methanol, and isopropanol and dried with nitrogen gas. The wafer was then loaded into the DRIE and etched according to the Bosch process. A combination of SF 6 and O 2 were used for etching while C 4 F 8 was used for passivation. Gas flow rate, power, and pressure were carefully selected to yield optimal geometries.

The wafer was transported back to the University of Pittsburgh for further processing. Both sides of the wafer were carefully cleaned with isopropanol and dried with nitrogen gas. An AMMT single series wet etching wafer holder was cleaned thoroughly with DI water and isopropanol, dried with nitrogen, and loaded with the black silicon wafer, lapped side up. A VWR water bath heated 5.36M potassium hydroxide solution to approximately 60±5°C. The wafer was submerged in the KOH for about 20 total hours. During this time, the wafer was periodically removed to be cleaned with acetone, methanol, and isopropanol, dried with nitrogen and measured with a micrometer to determine etch rate and visually inspect for defects. The wafer finished at a final thickness of 50±2 microns.

A second 500-micron <100> SSP c-Si wafer was wet etched, lapped side up, using the same procedure. The final thickness of this wafer was also 50±2 microns.

DATA PROCESSING Images were captured by a Zeiss Sigma500 VP SEM. Wafer thickness was measured by a Fowler digital counter micrometer. The ordinary thin film

and bSi thin film were each tested using a PerkinElmer Lambda 750 UV/Vis/NIR spectrometer to measure transmission, reflection, and absorption across the solar spectrum.

RESULTS As shown in figure 1a, the SEM images confirmed that the structures obtained from the DRIE process are indeed black silicon structures. Figure 1b shows how the nanostructures interact with incoming light rays to reduce reflection and create a uniformly black surface. a)

b)

Figure 1a-b: Black silicon surface images at the macroscopic scale (a) and the nanoscale (b). SEM center tilt 20°.

The results from spectrophotometer processing can be seen in figure 2. The planar thin film sample absorbs 54.2% of the solar spectrum (within the silicon bandgap), while the sample with bSi texturing indicates a significant improvement, absorbing 92.4% across the same spectrum. This remains true across the entire solar spectrum, proving that the combination of the two methods enhances all desirable effects.

Figure 2: This plot shows absorption for planar and bSi thin film across the silicon bandgap spectrum.

CONCLUSION By combining the light trapping effects of black silicon and thin film silicon, we were able to create an absorber with 92.4% spectrum absorption, which proved to be a significant improvement on standard thin film.

To further improve these results, actions can be taken to reduce waste and produce even thinner wafers. For example, an exfoliation method has been developed to create multiple thin film samples from a single bulk wafer [3]. Substituting this for wet chemical etching would yield significantly less material waste. Another means of reducing cost, especially on an industrial scale, would be to replace DRIE with an HF/AgNO3 etch [4]. A wet chemical etch would potentially be more scalable, and therefore more practical for large-scale manufacturing. Our lab is currently investigating this method and plans to continue its development.

REFERENCES 1. Wang, Y. (2016, May) KOH Etching of Silicon.

New Jersey Institute of Technology.

2. Janson et al. (1996) J. Micromech. Microeng. 6 14–28.

3. Saha et al. (2013) Single heterojunction solar cells on exfoliated flexible ∼25 µm thick monocrystalline silicon substrates. Appl. Phys. Lett.

102, 163904.

4. Liu et al. (2012) Nanostructure Formation and Passivation of Large-Area Black Silicon for Solar Cell Applications. Small, 8, No. 9 1392-1397.

ACKNOWLEDGEMENTS Special thanks to the PPG Foundation for funding my participation in this project. I would also like to thank the University of Pittsburgh Swanson School of Engineering, the Peterson Institute of Nanoscience and Engineering, Dr. Paul Leu, and Bradley Pafchek for providing me with the resources and guidance necessary to complete this project.

BINDER JET ADDITIVE MANUFACTUTING OF MAGNETOCALORIC FOAMS FOR HIGH-EFFICIENCY COOLING Katerina Kimes, Erica Stevens, Amir Mostafaei, Markus Chmielus Department of Mechanical Engineering and Materials Science University of Pittsburgh, PA, USA Email: kak272pitt.edu INTRODUCTION The magnetocaloric effect (MCE) is a phenomenon that occurs in many conventional magnetic materials where upon adiabatic magnetization, the material heats up and upon adiabatic demagnetization, it cools down [1]. The MCE was first discovered in the early 1900â&#x20AC;&#x2122;s and since then has been widely studied in an attempt to develop alloys that exhibit a large temperature change near room temperature in an effort to find a viable material for magnetic refrigeration (Figure 1). Environmental benefits and energy savings of up to 30% motivates the drive to advance magnetic cooling technology [2,3].

This study focuses on the AM method of Powder Bed Binder Jet (PBBJ) printing. In PBBJ printing, a metal powder is spread out one layer at a time and selectively joined with a binder after each layer (Figure 2) [4]. It then goes through a sintering process to burn off the binder and densify the sample.

Figure 2: Setup of typical PBBJ printer.

Due to the ability to control sintering effectiveness and therefore density in a PBBJ printed sample, it is possible to increase the surface area within the material by allowing interconnected porosity to remain. Therefore, a MC material with higher efficiency than traditionally manufactured parts can be aquired. In this study, a Ni50Mn18.75Ga25Cu6.25 Heusler alloy powder was produced, printed, and sintered. The densification and microstructure of the printed and sintered part was characterized.

Figure 1: Generalized magnetic refrigeration cycle using magnetocaloric materials.

Previous studies have been done to gather temperature and entropy data for many Ni-based magnetocaloric (MC) alloys. Although progress has been made in finding magnetic alloys that exhibit a large MCE near room temperature and in low magnetic fields, there have not been many studies regarding the additive manufacturing (AM) of Nibased magnetocaloric materials and how an AM process effects the functional behavior of the alloy.

METHODS High-purity elemental Ni, Mn, Ga, and Cu were cast into ingots using an induction melting process with a target atomic composition of Ni50Mn18.75Cu6.25Ga25.

The actual composition of the ingots was determined using a Zeiss Sigma 500 FESEM equipped with EDS. These ingots were broken into smaller pieces and mechanically ground into a powder using a Retsch PM100 ball mill. The powder was sieved to less than 106 Âľm. A Texas Instruments DSC Q10 was used to determine functionality and phase

transition temperatures of the powder. Printing was done using an ExOne Lab PBBJ printer. Coupons with target dimensions of 5 mm tall and 10 mm in diameter were printed. Samples were encapsulated in a quartz tube under an argon-purged vacuum atmosphere and sintered under two temperature conditions: 1000 °C, and 1020 °C for 2 hours followed by air cooling. A Ti getter was used for samples sintered at 1000 °C and 1020 °C and alumina support powder was used in one of two encapsulation tubes sintered at 1000 °C.

Table 2: Calculated densities of sintered samples Sample Density (g/cm3) Relative Density As-Printed 3.23 N/A 1000 °C 4.21 0.538 1020 °C 4.99 0.637

DISCUSSION Although ingots were homogeneous, the unexpected composition variation from ingot to ingot is due to Mn evaporation during melting. This can be accounted for by increasing the mass of elemental Mn before melting. The functionality of Heusler alloys are very sensitive to composition and a slight variation from the target composition may cause the effect to be weak to nonexistent. Thermal and magnetic measurements will need to be performed on the powder and the sintered samples in order to determine whether the functionality of the samples were affected by the composition variation due to induction melting.

Sample dimensions and masses were measured to determine densities. Imaging was done on a Keyence VHX-600 optical microscope, a Nikon Optiphot differential intereference contrast (DIC) microscope, and a Zeiss Sigma 500 FESEM. Composition was determined using EDS. RESULTS EDS results from 9 ingots are reported in Table 1.

Ingot compositions were homogeneous but varied unexpectedly from target composition.

The sintering study showed an increase in density with increasing temperature. It was determined that for coupons with relative densities around 50%, it is not necessary to use alumina powder because there is not significant shape change. The sintering study can be furthered by continuing to increase temperature until melting on the surface occurs and also decreasing the temperature slightly to obtain a strong sample with no melting. By performing more sintering studies, a model can be developed for the relationship between sintering temperature and density for this material. This can be helpful in the future for acquiring foams with specific densities.

Figure 3: DIC micrograph image of 1000 °C sample

Twinning in the sintered sample is indicative of martensite in the material. Therefore, this alloy has the potential to exhibit functional properties.

Calculated densities and relative densities for the sintered samples are reported in Table 2. The true density of the material, based on stoichiometry, was calculated to be 7.82 g/cm3.

REFERENCES 1. Liu et al. Nat. Mater. 11. 620–26, 2012.

2. Smith. The Euro. Phys. Jour. H. 38. 507–17, 2013.

3. Cherechukin et al. Phys. Lett. Sect. A Gen. At. Solid State Phys. 326. 146–51, 2004.

4. Mostafaei, et al. Mat. & Des. 108. 126-35, 2016.

All sintered samples were strong and did not easily scratch. Both samples sintered at 1000 °C with and without alumina retained their shape so it was determined that proceeding without alumina support powder would be best to avoid contamination. Figure 3 shows twinning in the 1000 °C sintered sample.

ACKNOWLEDGEMENTS Funding by PPG Foundation Undergraduate Research Program.

Table 1: EDS results for ingots used to make powder (wt%) Element Ni Mn Cu Ga

Ingot 1 47.85 16.46 6.36 29.33

2 46.01 16.00 9.02 28.98

3 47.27 16.65 7.95 28.12

4 44.95 15.83 9.15 30.08

5 46.58 15.69 8.33 29.40

6 43.60 15.57 9.23 31.60

7 47.53 16.05 8.14 28.28

8 47.71 15.75 7.95 28.59

and

Average 46.44 16.00 8.27 29.30

SSOE

BINDER JET ADDITIVE MANUFACTURING OF DENTAL MATERIAL FROM COBALTCHROME ALLOY Pierangeli Rodríguez, Amir Mostafaei and Markus Chmielus Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA, USA Email: pir6@pitt.edu, amir.mostafaei@pitt.edu, chmielus@pitt.edu INTRODUCTION Additive manufacturing (AM), also known as threedimensional (3D) printing, is the process of selectively adding material, usually binding one layer to the next, to create an object according to the model data. AM allows to directly manufacture parts with complex internal and external geometries out of a wide variety of materials (metal, polymer, ceramic, sand and glass) while reducing material and chemical waste and increasing control of part size and shape [1]. Binder jet printing (BJP) holds distinctive promises among AM technologies due to its fast, low-cost manufacturing, stress-free structures with complex geometries.

Co-Cr-Mo is a commonly used alloy in fields requiring high heat and corrosion resistance as well as in medical and dental applications because of its advantageous properties (resistance to corrosion, high specific strength, heat resistance, and biocompatibility). This alloy is, thus, used to build heavy machinery as aircraft jet engines, and body replacement parts like prosthetic implants and dental frameworks. Increasing interest in this compound surges in regards of this last application; the urge to replace Ni-Cr alloy-based dental frameworks, whose ions can be toxic when released in the oral cavity [2].

This need led to an interest in studying 3D printed Co-Cr-Mo and its potential applications for denture frameworks.

The objective of this project is to understand how different sintering temperatures affect the porosity reduction of printed Co-Cr-Mo parts to improve its mechanical properties. Initially, literature was reviewed to better choose sintering conditions.

Porosity distribution, density and hardness of the asprinted and sintered samples were studied.

METHODS For this project, gas-atomized alloy Co-Cr-Mo powder (supplied by Carpenter Technology Corporation, Figure 1) was used to manufacture 3D printed parts, using X1-Lab ExOne printer.

Figure 1. SEM micrograph of the Co-Cr powder.

Cylinders of (diameter of 1 cm and height of 1 cm) were printed in groups of 12. Printed parts were cured at 200 °C in a Carbolite oven (type PF30) for at least 8 h and then sintered in a Lindberg tube furnace (three samples per sintering temperature where submerged in an alumina powder bed under vacuum) with the following heating profile: (1) Heating by 5 °C/min from room temperature to 1000 °C, (2) Heating by 2.5 °C/min to the holding temperature (from 1240 to 1380 °C with interval of 20 °C), (3) Holding the desired temperature for 2 h, (4) Cooling by 1 °C/min to 1225 °C, (5) Cooling by 5 °C/min to 500 °C and finally furnace cooling.

Density and dimension changes were measured, on both as-printed and as-sintered samples, according to the Archimedes principle, using an OHAUS AX324 precision balance (0.1 mg resolution). Archimedes densities of each sintering temperature were averaged and normalized by density of Co-Cr-Mo (8.439 g/cm3). ImageJ analysis included the calculation of the area occupied by the pores in each of the random optical micrographs taken. This porearea was subtracted from 1 as it is opposite to the density. Both densities calculations were graphed together, to observe the density vs. sintering temperature curve, and the consistency of the measurements.

For microstructural examinations, one sample of each sintering temperature was cut (cross section), cold mounted, grounded and polished (using a Struers Tegramin-25 automatic system). Then, optical micrographs were taken with a Keyence digital optical microscope (OM). Densities were recalculated with ImageJ (image analysis software), and compared with Archimedes densities.

Vickers microhardness tests were also performed on the cross sections of samples with a Leco LM 800 microhardness tester (100 gf for 10 s). Vickers microhardness results were also averaged and plotted.

was a low peak at 1320 °C of 81.6 ± 23.9 HV 0.1 . This disparity is explained by M. Dourandish, because varying contributions to the hardness are dominant at different sintering conditions affecting density measurements: “with increasing sintering time and temperature, grain growth or coarsening and segregation of alloying elements to the grain boundary has opposite effects on the hardness” [3].

RESULTS Relative density results according to Archimedes principle and ImageJ analysis are summarized in Figure 2. With increasing sintering temperature, the density of the samples increased and the volume decreased. The average green density was 44.1%.

Then by Archimedes principle the relative density increased from 52.9% to 64.4% from 1240 °C to 1320 °C, with a change of about 3 % every 20 °C increment in sintering temperature. The highest density (97.5%) was reached at 1380 °C. ImageJ results, are mostly coherent with the previous results, but more accurate: the density increased from 56.5 % (sintered at 1240 °C) to 99.1% when sintered at 1380 °C. The variation between image analysis and water displacement method can be explained by some imbedded alumina powder particles that affected the Archimedes method measurements, by blocking the penetration of water in the sample [1].

1. It is possible to achieve nearly fully densified BJP Co-Cr-Mo parts under the right sintering conditions, (1380 °C for 2 h). OM showed that the sample reached the optimal densification temperature as practically no pores remained and the grain boundaries were filled with precipitate “probably liquid phase formed during sintering” [1].

2. Pore interconnection decreased when sintered from 1340 °C on, and pore size increased for the 1360 °C sample, this change is explained because “Differences in the pore curvature lead to growth of the large pores at the expense of the smaller stable pores” [3].

3. Hardness values increased with increasing sintering temperature, reaching a maximum value of 295.2 HV 0.1 at 1380 °C.

Figure 2. Relative densities of samples at each sintering temperature from 1240 °C to 1380 °C, according to Archimedes method and ImageJ image analysis.

Microhardness results also increased with the sintering temperature from 92.7±35.3 HV 0.1 (at 1240 °C) to 292.1 ± 16.0 HV 0.1 (at 1380 °C). There

DISCUSSION In this study, Co-Cr-Mo alloy samples were successfully printed using powder bed binder jetting.

The following statements were concluded:

REFERENCES [1] A. Mostafaei, E.L. Stevens, E.T. Hughes, S.D. Biery, C. Hilla, M. Chmielus, Powder bed binder jet printed alloy 625 : Densification , microstructure and mechanical properties, J. [2] W. Yu, C. Qian, W. Weng, S. Zhang, Effects of lipopolysaccharides on the corrosion behavior of Ni-Cr and Co-Cr alloys, J. Prosthet. Dent. 116 (2016) 286–291.

[3] M. Dourandish, D. Godlinski, A. Simchi, V. Firouzdor, Sintering of biocompatible P/M Co-Cr-Mo alloy ( F-75 ) for fabrication of porosity-graded composite structures, Mater.

Sci. Eng. A. 472 (2008) 338–346.

ACKNOWLEDGEMENTS Thanks to all the Chmielus Lab group, especially Amir Mostafaei and Dr. Chmielus, and to the Swanson School of Engineering and the Office of the Provost.

Density Variation in Additively Manufactured Ti-6Al-4V Samantha Schloder, Erica Stevens, David Schmidt, Markus Chmielus Advanced Manufacturing and Magnetic Materials Laboratory Department of Mechanical Engineering and Material Science University of Pittsburgh, Pittsburgh, PA, USA Email: sas332@pitt.edu, Web: Chmieluslab.org INTRODUCTION Additive manufacturing (AM) is another name for the 3D printing of parts. One example of metal AM processing is powder bed binder jet printing, where products are manufactured from three-dimensionally modeled designs. During this process a binder is added to the powder of each stacked layer according to the 3D model, thus, producing a green part in a complex shape [1]. This process makes a part that is loosely held together by the binder and requires further processing to increase strength and density.

How a green part is bound together before postprocessing will greatly affect the microstructure of the finished product and, thus, the mechanical properties as well [2].

Historically, titanium products have been machined from forged titanium blanks due to properties such as reactivity [3]. Binder jet printing is an important AM method for titanium alloys because unlike laserbased methods, reactivity is less of a concern as there is limited heating. In this research study, Ti-6Al-4V, which is the most commonly used titanium alloy, was 3D-printed using powder bed binder jet printing then sintered in post-processing [4]. The uniformity of the densification is examined.

METHODS The printed and sintered sample shown in Figure 1 was cut on a bandsaw, to produce a slice of material that was further cut in smaller pieces by a metallographic saw for hot mounting. a

b

Figure 1: Complex shape manufactured by Carpenter Technologies out of Ti-6Al-4V. (a) shows a side view. (b) shows a top view, indicating where the slice was cut out.

Samples were imaged on a Keyence VHX-600 at 100x magnification. All micrographs were merged to resemble the original slice as much as possible even though a small amount of material was lost due to cutting. The reassembled slice was split up into a 7x2 grid of sub-images for ImageJ analysis [5]. Each picture was individually thresholded and a batch macro was written that systematically split up an image into a 20x20 grid, each with dimensions of 617x555 μm². ImageJ was then used to calculate the amount of material present locally.

After the batch macro was used to process the original thresholded sub-image, the same sub-image underwent a process that would make the piece appear to be completely dense. The procedure used the commands fill holes and dilate, done i times until the part was solid, then using the command erode i times until the edges of the piece were back to their original state. When eroding was done, the edges of the sample that fall along the image’s boundaries were reduced i times and manually corrected for. The batch macro was used again to spilt up the sub-image and measure the area of the sample that was manually solidified. Figure 2 shows an example of the original thresholded image and the manually densified image from the same location on the sample.

a

b

Figure 2: (a) and (b) are an example of the images that result from running the batch macro. Each image is 616.81x504.67μm. (a) shows the area of the original thresholded sub-image and (b) shows the area of the manually densified sub-image.

Finally, the variation in density along the original part was found using the equation density = (area of solid sample in original image)/(area of solid sample in manually solidified image). By mapping out the

resulting density values, a representation of density distribution along the part can be seen.

RESULTS Density measurements ranged from a low of 19.5% to a high of 100.0%. The low value of 19.5% was a localized minimum and pertained to such a small area that it was excluded from the mapping in Figure 3, so that the variations on the sample could be more defined. Across the sample, the mean density was 81.9 ± 11.1% and the median density was 84.2%.

The most visible difference along the sample would be the changes in color seen when comparing the flat edges to the curved section. Along the flat edges values are seen to be in the 40%-70% range, while along the curve values rarely ever fall below 70%.

There was a consistent trend of lower densities along the outside edge of the sample.

Printing Axis

related to the process of wet granulation found in the pharmaceutical industry. Wet granulation is done by adding a liquid solution onto a powdery material so that the particles will stick together similarly to binder jet printing. Studies have found that two major mechanisms exist between drop and powder, which are spreading and infiltration [7]. Spreading is how much area the liquid binder encounters when added to the powder particles, while infiltration refers to how much binder enters the powder particles. When spreading occurs, there would be more area that is coated in binder that is not necessarily desired. If spreading were to occur, there would be less binder in that layer available to infiltrate the powder particles, resulting in this layer not being as held together as possible. These mechanisms could be causing the lower densities seen along the edges of the sample.

To finally determine the reason for the local density changes, an additional study on the local green density and binder distribution will be needed.

REFERENCES

Figure 3: Mapping of the density values of a cross-sectional area of the sintered Ti-6Al-4V sample with printing axis shown in respect to the piece. Values near 20% were considered outliers and excluded from the map to improve visibilities of other variations. Some material was lost during cutting, resulting in some discontinuities.

DISCUSSION There are three potential reasons for the variation in density in the sintered part: (1) a variation in sintering temperature and, therefore, densification kinetics during sintering, (3) variations in the powder spreading and (3) variation in the binder density.

The low-density areas at the right and left end of the sample (Fig 3) are likely due to a lower temperature in the sintering furnace in these regions, resulting in a slowed densification.

Excluding these two areas of localized minimums, there are two clear trends: one trend is the less dense area found on the outside edges, while the second trend is how the curve seems to be the densest. Both trends point towards being a result of the printing process which influences all properties of the green and sintered part as reported by Chen and Zhao [6].

Although research on binder penetration in powder bed binder jet printing is scarce, the process can be

[1] W. E. Frazier, “Metal additive manufacturing: A review,” J. Mater. Eng. Perform., vol. 23, no. June, pp. 1917–1928, 2014.

[2] K. V Wong and A. Hernandez, “A Review of Additive Manufacturing,” ISRN Mech. Eng., vol.

2012, pp. 1–10, 2012.

[3] Qian, M., Xu, W., Brandt, M., & Tang, H. P. Additive manufacturing and postprocessing of Ti-6Al-4V for superior mechanical properties, 775-784.

[4] M. Donachie, Titanium : A Technical Guide (2), 2nd ed. ASM International, 2000.

[5] C. A. Schneider, W. S. Rasband, and K. W. Eliceiri, “NIH Image to ImageJ: 25 years of image analysis,” Nat. Methods, vol. 9, pp. 671–675, 2012.

[6] H. Chen and Y. F. Zhao, “Process parameters optimization for improving surface quality and manufacturing accuracy of binder jetting additive manufacturing process,” Rapid Prototyp. J., vol. 22, no. 3, pp. 527–538, Apr. 2016.

[7] H. R. Charles-Williams, R. Wengeler, K. Flore, H. Feise, M. J. Hounslow, and A. D. Salman, “Granule nucleation and growth: Competing drop spreading and infiltration processes,” Powder Technol., vol.

206, no. 1–2, pp. 63–71, 2011.

ACKNOWLEDGEMENTS The authors would like to thank Carpenter Technologies for materials, the PPG Foundation for funding and SSOE for supporting undergraduate research.

Sequential Infiltration Synthesis for Hierarchical Nanostructure Coating Katherine A. Brosky Energy and Materials Laboratory, Department of Material Science University of Pittsburgh, PA, USA Email: kab346@pitt.edu, Web: http://www.engineering.pitt.edu/MEMS/ INTRODUCTION The efficiency of solar cells depends on the attachment of the perovskite layer and how well metal particles can lay in the perovskite to increase conductivity. In order to create a higher efficiency solar cell, nano-morphologies are manually created between the substrates surface and the perovskite layer. Sequential Infiltration Synthesis is a delicate process that uses polymer solutions to create nanostructure morphology on a substrates surface.

Such morphologies are restricted to the type of polymers used, homopolymers or copolymers.

Homopolymers have an advantage over block copolymers in that they are an extremely cheaper material. The primary aim of this article is to contribute to the understanding of the impact of homopolymers blends to Sequential Infiltration Synthesis. Specifically, understanding how the homopolymers PS and PMMA can interact in solution to create a desired morphology.

Ton-That et al. examined morphology created by effects of Homopolymer Blends using a mica substrate pretreated with ozone; they observed granular and pitted morphologies depending on the ratio of Polystyrene and Poly(methyl methacrylate) [1]. Further studies, including Frascoli et al., have observed the effect of combining homopolymers and copolymers in solution, the pretreatment of ozone, and RTP annealing to produce a desired morphology [2]. Only one article ever addressed methods using strictly homopolymer blends not mixtures of homo and co polymers. Therefore, combining the efforts of Frascoli and Ton-That gave greater understanding on how Sequential Infiltrtaion synthesis can be accomplished using solely homopolymers.

METHODS The experiment consisted of cleaned FTO substrate that was pretreated with 15 min of ozone to increased adhesion of the polymer solution. The Homopolymer Solution was created in a 1:1 mol

ratio of PS (MW 280 000) and PMMA (350 000) with chloroform as the solvent. The solution must be sonicated for a total 15min with 5min each sonication in order to dissolve while not harming the polymers. In other words, Two half solutions are made, one PS in half the total amount of chloroform and one PMMA in half the total amount of chloroform. Then, the two half solutions are sonicated for two 5min sonication sessions. Once the two solutions are uniform, combine the two half solutions to make one total solution and sonicate for another 5min.

After the substrate was cleaned and pretreated with ozone, the solution was spin coated onto the substrates surface at 3000rpm for 2min. A maximum of 40ml was spin coated onto the substrates surface. This process was repeated in various techniques to achieve the most uniformity on the surface. Other methods such as dip and spin casting were attempted, but spin coating achieved the best results as far as a uniform solution layer.

The next step in Sequential Infiltration Synthesis, once the polymer layer is created, is to deposit Atomic Layering Deposition (ALD) on top of the rigid polymer layer. In essence, the polymer layer creates the morphology on the substrate, and the ALD, composed of even more rigid metal oxides, maintains the morphology. Thermal ALD deposited TiO2 at 130℃ for ~ 3hrs.

Lastly, Annealing occurs in order to remove the excess polymer and allow solely the TiO2 to remain.

Two techniques were attempted: RTP annealing and annealing in a vacuum. RTP annealing occurs at 200℃ in Nitrogen ambience for 5hrs [2]. The annealing in a vacuum occurred at 400℃ for ~ 1hr.

DATA PROCESSING Characterization of the morphologies were taken under SEM and Optical profiler imaging. Images were taken along each step of the process (after the

solution was coated, after ALD was deposited, and after annealing occurred) in order to give a better understanding of morphology formation. The best images of the horizontal morphology (features on the surface) occurred with SEM when magnification occurred at 10XK and the scale was set to 2um. The best images of the vertical morphology (thickness) occurred with optical profiler at maximum magnification (50).

RESULTS Overall, the best images occurred from a solution of 20.9mg PS and 26.1mg PMMA were dissolved in 4mL chloroform. This trial was examined using SEM and optical profiler after ALD was deposited and before annealing occurred.

The characterization seems to show small pit like formations ~500nm in diameter, and a film thickness of ~200nm. On average, most pit formations were ~1um in diameter. Figure 1 below displays a pitted morphology under SEM using 10XK magnification at a scale of 2um.

Figure 1: Morphologies on FTO substrate examined by SEM. These structures were produced by 1:1 mol ratio PS:PMMA solution after ALD before annealing.

Figure 2 below displays the Optical Profiler image of the sample from Figure 1. The dark blue regions shows the pits and the light green shows the higher elevated regions. Overall, the uniform film thickness is around ~200nm.

Figure 2: Image of the surfaceâ&#x20AC;&#x2122;s thickness and morphology in the y-plane. The blue image is a surface image of the pits with topographical scale. The charts below give exact numerical definition of the x and y profile of the film and pitted morphology.

DISCUSSION The pitted morphology was expected due to the 1:1 mol ratio of PS:PMMA in solution [1].

Additionally, the pitted morphology is due to the wettability, rigidity, and hydrophilic and phobic nature of each polymer in the system. The pitted morphology would occur due to the use of only one film, or one solution. As explained by Ton-That et al., the wettability of a films is determined by the spreading coefficient. The spreading coefficient is S=g2-(g1+g12); when S<0 complete wetting occurs, and when S>0 partial wetting occurs [1].

However, because g1 and g2 represent the surface tension of the two films, g12 remains because it represents interfacial surface tension. Therefore, the hydrophobic nature of PS and hydrophilic nature of PMMA will repel and attract during wetting to create a pitted morphology.

In essence, more research must be done to reduce thickness and diameter of pits for production of solar cells, although this process proves pitted morphology can be achieved at a nano-morphologic scale.

REFERENCES 1. Ton-That et al. Polyme,r 43, 4973-4977, 2002.

2. Frascaroli et al. ACSpublications, 49, 3393333942, 2016.

ACKNOWLEDGEMENTS Thanks to PPG, samples were created and examined at the University of Pittsburgh Energy and Material Sciences Laboratory.

MATERIALS COMPUTATION OF MAGNETIC PROPERTIES OF COBALT NANOPARTICLES Alexandra Beebout Laboratory of Dr. Guofeng Wang, Department of Materials Science University of Pittsburgh, PA, USA Email: alb305@pitt.edu INTRODUCTION Magnetic nanoparticles are an important research topic because they are useful in a variety of applications, namely, data storage, biotechnology, medical imaging, magnetic fluids, catalysis, and environmental 1 remediation. The study of transition-metal clusters is helpful in understanding the behavior of 3d electrons, which are responsible for ferromagnetism. Cobalt is of particular interest as it is most widely used in hard drives and has potential to be used as a high-temperature coating in solar panels.2 Research on the geometric and energetic properties of small cobalt clusters has proven difficult, as the scale in question is too small for diffraction probes and too large for spectroscopic analysis.

The complex magnetic behavior of free cobalt clusters (N = 20 â&#x20AC;&#x201C; 200) has been reported on by J. Bucher, D. Douglass, and L. Bloomfield.5 Cobalt exhibits at least four distinct crystal structures, these being FCC, HCP, icosahedral, and epsilon-cobalt.3,6 The first to synthesize and describe epsilon cobalt were D. Dinega and M.G. Bawendi via thermal decomposition of octacarbonyldicobalt in the presence of trioctylphosphane oxide.3 J. Souto-casares et al. Used real-space formalism of pseudopotentials within DFT calculations to investigate the magnetic and geometric properties of cobalt clusters; they concluded that icosahedral and HCP structures were most stable on this scale.4

(a)

(b)

(c)

(d)

(e)

(f)

Figure 1: VESTA representations of cobalt clusters. (a) FCC n=147, (b) icosahedral n=13, (c) HCP n=153, (d) icosahedral n=55, (e) epsilon-cobalt n=153, (f) icosahedral n=147,

Our research explores magnetic and energetic properties of the four observed structures of cobalt clusters. It will fill a gap in current research on magnetic nanoparticles.

METHODS We performed density functional theory (DFT) calculations on the software known as Vienna Ab initio Simulation Package (VASP) using pseudopotential plane wave method. Data files that modelled and described analytically the clusters were produced via Visualization for Electronic and Structural Analysis (VESTA)

software. Examples of the structures modelled using this software can be found in Figure1. To begin we applied geometry optimization to clusters of cobalt atoms, N = 13 – 155, of three known crystal structures in order to determine geometric and energetic parameters. We compared our results to those of similar calculations performed by other research groups.

(a)

We then moved on to energy optimization calculations using projector augmented wave method. A conjugate-gradient algorithm was used to relax the ions into their instantaneous ground state until all force components decreased to less than 0.01 eV/Å. Our method used the PerdewWang 91 exchange-correlation functional for spin-polarized generalized gradient approximation (GGA) in which the 3d and 4s electrons are treated as valence electrons.

The wave functions are expanded in the plane wave basis set with the kinetic energy cutoff of 500 eV. We set the initial magnetic moment per atom to 5.

(b)

RESULTS From the calculations we obtained groundstate energy and magnetic moment values for all four crystal structures: FCC, HCP, icosahedral, and epsilon. These values were calculated for three different cluster sizes, N=13, N= (55,57,59), and N=(147,153). The results are displayed comparatively in Figure 2. Our results indicate that the icosahedral structure is the most stable, as its relaxed structure consistently exhibits the lowest energy. This is in agreement with results published by J. Souto-casares et. al.4 Furthermore, we observe that as the cluster size increases in the relaxed structures, the energy and magnetic moment per atom decrease. Smaller particles therefore impart a much higher magnetic moment and energy per atom.

Figure 2: Calculated values for all four crystal structures. (a) Total energy of the relaxed cluster divided by the number atoms (n) plotted against n. (b) Total magnetic moment of the relaxed cluster divided by the number atoms (n) plotted against n.

REFERENCES [1] A.Lu, E. Salabas, and F. Schüth, (2007), Angewandte Chemie International Edition, 46(8), 1222-1244 (2007).

[2] J. Moon , T. K. Kim , B. VanSaders , C. Choi , Z. W. Liu , S. H. Jin , and R. K. Chen , Sol. Energy Mater. Sol. Cells 134, 417 (2015).

[3] D. P. Dinega and M. G. Bawendi, Angew.

Chem., Int. Ed. Engl. 38, 1788(1999).

[4] J. Souto-Casares, M. Sakurai, and J. R. Chelikowsky, Phys. Rev. B 93, 174418 (2016).

[5] J. P. Bucher, D. C. Douglass, and L. A. Bloomfield, Phys. Rev. Lett. 66, 3052 (1991).

[6] Q.-M. Ma, Z. Xie, J. Wang, Y. Liu, and Y.-C. Li, Phys. Lett. A 358, 289 2006 .

ACKNOWLEDGMENTS This research was made possible by the Swanson School of Engineering and funded in part by PPG Industries, Inc.

The effect of a Perovskite/TiO2 interface on I-V Curves, Retention, and Endurance properties in a Bi-Layer ReRAM Device.

Sarah Wolfe, email svw4@pitt.edu Jung-Kun Lee research Laboratory, Mechanical and Materials Science Department University of Pittsburgh, Pittsburgh PA

Introduction Resistive Random Access Memory devices (ReRAM) are widely regarded as the next generation of memory devises. They are nonvolatile, have a fast operation/switching speed and have good scalability [1]. ReRAM devices are often set up in Metal Insulator Metal (MIM) structures. Many ReRAM devices use Perovskite as the insulating layer.

The insulating layer is where the switching behavior of the device happens. Though it is not completely understood it is commonly believed that resistive switching in Perovskite happens due to movement of ions within the layer that connect to form conductive filaments [2].

Typically a ReRAM device will only have one layer between the two metal electrodes.

The aim of this research was to see how the addition of another layer, which brings another interface, affects the switching behavior and ReRAM properties of the device.

For this purpose a thin layer of TiO 2 was added to the Perovskite layer in the device.

The additional interface was expected to affect the set/rest voltage, the on/off current ratios, the general shape of the I-V curves, the amount of time needed for the retention test, and the current in the endurance test. For this project the device structure was a glass substrate coated with FTO, a layer of TiO 2 (at varying thickness), a layer of Perovskite (at varying thicknesses), and Au electrodes, see figure 1.

Figure 1: Device Structure

Methods The ReRAM devices were fabricated by cutting glass covered in FTO into 2 cm x 2 cm squares,

cleaning, and then an Ozone treatment. Some samples had a layer of TiO 2 deposited via plasma Atomic Layer Deposition (ALD).

The Perovskite was made using a one step process.

159 µg of MAI was mixed with 76 µL of DMSO, then 461 µg of Pb 2 was added. Finally either 1 mL or 580 µL of DMF, for a 200 or 400 nm layer respectively, was added. The solution was then mixed for half an hour on a stir plate before spin coating. Spin coating lasted a total of 25 seconds and 8 seconds in ethyl ether was added to the device, .2 mL for 200 nm thickness and .4 mL for 400 nm thickness.

I-V sweeps were done using the pre-set test and were swept between 2 V and -2 V. The endurance and retention tests were programed using the direct control tests. The retention test was performed at .5 V and the endurance test had the voltage pulse between 2 V and -2 V.

Results There were six different conditions tested: MAPbI 3 (200 nm) with a 12 nm, 6 nm, 0 nm layer of TiO 2 , and MAPbI3 (400 nm) with a 12 nm, 6nm, 0 nm layer of TiO 2 . The I-V sweep test was performed on all electrodes and then several electrodes from each sample were chosen to have the endurance and retention tests performed on them.

Figure 2: I-V curves for MAPbI3 (200 and 400nm) For samples without TiO 2 the large change in the current, or hysteresis loop, if there was a change, occurred when a positive bias was applied.

Typically the 200 nm sample showed a large hysteresis under the positive bias and the 400 nm sample tended to not show a large hysteresis.

4.00E-04

changed the representative circuit of the device.

Adding the TiO 2 layer is like adding another resister in series. This new resister changes how much voltage is applied to the different layers depending on the thickness of the layer. The thicker layer of MAPbI 3 , 400 nm, resulted in a smaller difference between the currents in the hysteresis loop. A smaller difference in the hysteresis current drop is also observed in both cases when the layer of TiO 2 is 6 nm, compared to 12 nm. Additionally it is observed that the thickness of the TiO 2 has a more profound effect than the thickness of the MAPbI3 layer. This can be seen from the drastic jump in the on/off current ratios for the MAPbI 3 400 nm samples. With a 6 nm layer of TiO 2 the ratio is about 10x but in the 12 nm case the difference is about 100x. The difference in the 200 nm case between the two TiO 2 thicknesses is not as drastic. This indicates that the thickness of the TiO 2 has a larger impact on the current/voltage distribution than the thickness of the MAPbI 3 does.

One aspect that the thickness of the TiO 2 and the MAPbI3 has little to no effect on is the set/reset voltage. In all cases the set/reset voltage is approximately -1.5 V, but it can vary between -1.5 and -1.2 V.

2.00E-04

Conclusion

Figure 3: I-V curves for MAPbI3 (200 and 400 nm) with a 6 nm and 12 nm layer of TiO 2 .

For the samples that had a layer of TiO 2 the hysteresis shifted so that it showed when a negative bias was applied. And both MAPbI3 thicknesses showed a hysteresis loop as opposed to the pure MAPbI3 cases.

Figures 4 and 5 show an example of the data obtained with the retention and endurance tests respectively.

Current

MAPbI3(40nm)+TiO2(6nm)

0.00E+00 0

500

1000

Time (sec)

Figure 4: Retention test, Held at .5 V for 1000 sec.

MAPbI3(400nm)+TiO2(6nm)

voltage 4 2 0 -2 -4 3

Voltage

Current

0.05

current

0

-0.05 0

1 Time (sec) 2

Figure 5: Endurance Test. Pulsed between -2 ->2 V.

Discussion From comparing the I-V curves in figure 2 and 3 the first noticeable effect of the additional TiO 2 interface is switching which basis activates the hysteresis loop. In the case of pure MAPbI 3 the loop was activated by the positive bias. But once the TiO 2 is added the loop is present when negative bias was applied. The additional interface also

The additional interface that the TiO 2 provides affects the I-V curves of a bi-layer ReRAM device.

(1) The addition of the TiO 2 makes the bias that activates the hysteresis loop change, from positive to negative. (2) The thicknesses of both layers affects the on/off current ratio. A thicker TiO 2 layer gives a larger ratio but a thicker MAPbI 3 layer yields a smaller ratio. (3) Neither layerâ&#x20AC;&#x2122;s thickness had an effect on the set/rest voltage, which was consistently around -1.5 V. Therefore the ideal dimensions for a MAPbI 3 /TiO 2 bi-layer ReRAM devices is: MAPbI3 -200 nm and TiO 2 -12 nm.

References [1] Gu, Chungwan, and Jang-Sik Lee. Flexible Hybrid Organic-Ionorganic Perovskite Memory.

2016 [2] Kwon, Deok-Hwang et all. Atomic structureof conduction nanofilaments in TiO2 resitive switching memory. 2010.

Acknowledgments Thank you to PPG Foundation for sponsoring this research. And To Dr. Lee for sponsoring this project.

THE EQUIVALENTS BETWEEN REYNOLDS NUMBER AND RAYLEIGH NUMBER IN CYLINDER Junbo Wang, Hessam Babaee Department of Mechanical Engineering University of Pittsburgh, PA, USA Email: juw66@pitt.edu INTRODUCTION In natural convection, the Nusselt number is correlated with Prandtl number and Rayleigh number. In forced convection, the Nusselt number can be expressed as a function of Prandtl number and Reynolds number.

Texas Advanced Computing Center stampede, at The University of Texas at Austin. By using python program, sixty-four pairs of Prandtl number and Reynolds number were selected and wrote into stampede.

After running the program for two hours, Nusselt numbers were created. To get the mean value for the Nusselt number, Matlab was used to sort those number and find the mean value based on different pairs of Prandtl number and Reynolds number. By comparing the Nusselt number from the simulation to the experiment equation, the Nuseelt number was verified.

Lemlich and Hoke in 1956 utilized the concept of equivalent by finding Nusselt number distribution on natural convection over a haot cylinder is similar to the forced convection. Both Rayleigh number and Reynolds number are dimensionless quantities in fluid mechanics used to help predict flow patterns in different fluid flow situations. Acrivos(1966) illustrated the following equivalence between different dimensionless group that result the same local Nusselt number:

By finding the equivalent between Rayleigh number and Reynolds number, it could be easier to predict the same Nusselt number between natural convection and forced convection.

METHODS To study the forced convection and natural convection, the program nectar was used in both simulation. The program was running under the

To find the relation between Rayleigh number and dt. Set Pr=2 and NStep=3000 at mode 6; run several cases on the head node for different Rayleigh numbers in the range of [1, 40000].In each case, change dt such that the CFL number settles to a steady state and less than 0.8 Use Matlab to curve fit the data and find Ra vs dt. Last, Comparing the correlation for Ra vs Nu and Re vs Nu and find the equivalents between Re and Ra. DATA PROCESSING The relation between Re and Nu was found by taking average of the last 20000 data. Eight graph was plotted based on different Pr number.

Comparing the direct numerical simulations with the correlation equation as below, DNS may be slightly lower than the correlation.

To find the Ra vs dt, First set the Pr number to 2 and choose mode 6 to run the simulation. Set the Nstep equals 3000, since the running time is small enough, the code can be running under the head node. In this process, it is important to make sure the CFL number stay as close as possible to 0.8 by

changing the dt. The correlation equation for Nu vs Ra is as below

RESULTS In the forced convection, the relation between Re and Nu is shown below. Correlation is higher than DNS due to temperature complex and the chosen of period amount of time.

Figure 2: The relation between Ra and dt can be represented as:

Figure 1: In forced convection, Re vs Nu at Pr=2.

Red, purple and blue line represent DNS; Green line represent the correlation.

The following table is the experiment Ra vs different time period by control the CFL number close to 0.8.

Table 1: Ra vs experiment dt at controlled CFL number.

DISCUSSION Finding the equivalents between Ra and Re is significant. This process could contribute on predicting the same Nusselt number between natural convection and forced convection. During the experiment process, the code blow up. It is because when the simulation was running on higher mode, the temperature diverged. By lowing the dt from 5e-3 REFERENCES 1. ACRIVOS, A.1966 On the combined effect of forced and free convection heat transfer in laminar boundary layer flows. Chem. Engng Sci. 21 (4), 343-352 2.CHURCHILL, S. W. 2014 Equivalents â&#x20AC;&#x201C; a new concept for the prediction and interpretation of thermal convection. Ind. Engng Chem. Res. 53 (10), 41041-4118.

3.BABAEE, H. Perdikaris, P.etc. 2016 Multifidelity modelling of mixed convection based on experimental correlations and numerical simulations. J. Fluid Mech. Vol. 809, 895-917 ACKNOWLEDGEMENTS This work is supported by Texas Advanced Computing Center under Professor Babaeeâ&#x20AC;&#x2122;s account. The research is being funded by the Swanson School of Engineering and the Office of the Provost.

THE EFFECT OF PROCESS PARAMETERS ON THE TENSILE STRENGTH OF 3D PRINTED ABS AND PLA Marissa A. Wolfe Department of Mechanical Engineering, National University of Singapore, Singapore 117575 Email: maw239@pitt.edu INTRODUCTION 3D printing offers the flexibility to change the design, material, and process parameters for specific 3D printed samples. However, adjusting these settings can change the mechanical properties of the piece being printed. This paper analyzes the effect of print angle, layer thickness, nozzle diameter, and infill percentage on the tensile strength of 3D printed ABS and PLA thermoplastic samples.

ABS and PLA are common thermoplastics used in 3D printing. Acrylonitrile Butadiene Styrene (ABS) has high strength, flexibility, machinability, and high temperature resistance that makes it the top choice for 3D printing mechanical applications.

However, it has a very high melting point, and it is known for experiencing warping during printing (Grieser, 2017). Polylactic Acid (PLA) is formed from organic materials which makes it easier and safer for use. Because of its lower melting point, it cannot be used to manufacture parts that need to be kept in high temperature locations. (Ramon, 2017).

Fused Deposition Modeling, known as FDM, is a common type of 3D printing and was utilized during this experiment. In an FDM printer, plastic filament, such as ABS or PLA, is fed through a nozzle where the material is liquefied and drawn onto a platform where it hardens. The platform lowers by one layer thickness so the nozzle can start on the next layer (Fabian, 2015).

METHODS Table 1 displays the testing parameters chosen for analysis during this research. Data points were selected that reflect common 3D printing practices and specifications available among 3D printers.

Standards for tensile testing utilize an end tab test specimen. ASTM D638 is the standard for material testing of plastics for additive manufacturing (Forster, 2015). For this experiment, type IV of this specimen was selected. The specimen was modeled in SolidWorks and converted into an STL file that can be read by the 3D printing software. For these experiments, Simplify 3D software was used to change the printing parameters of each sample.

Printing was conducted on the Moment 3D printer for the ABS samples and the FlashForge Creator Pro 3D printer for the PLA samples.

For each 3D printed sample, tensile testing was performed. The tensile machine outputs the load and the extension experienced by the sample until fracture occurs. From this data the stress, strain, ultimate tensile stress, and Young’s modulus for each sample could be calculated.

RESULTS RASTER ANGLE 0/90 Young’s modulus and the Ultimate Tensile Strength (UTS) were higher in the PLA than ABS samples for all specimens with the same printing parameters.

For example, at 50% infill, 0.2LT, and 0.4ND the PLA sample had a Young’s modulus and UTS of 1947 and 21.9 MPa respectively, whereas the ABS sample had a Young’s modulus and UTS of 1244 and 15.7 MPa respectively. This trend was consistent for all 0/90 samples with mirroring parameters. There was significantly more necking observed in the ABS samples. This is indicative of the fact that it is a less brittle material than PLA.

Table 1: Testing Parameters Testing Parameter

Data Points Analyzed

Material Layer thickness (LT)

ABS and PLA 0.2 and 0.3 mm

Nozzle Diameter (ND) Printing Angle (%)

0.3 and 0.4 mm 0/90 and 45 degrees

Figure 1: UTS vs Nozzle Diamater for PLA 0/90

layer thickness. Unlike the samples printed at 0/90 there was a clear trend that UTS increases as strength increases. This is true for all samples except one set of samples that seem to have a negligible difference in UTS.

Figure 2: UTS vs Nozzle Diameter for ABS 0/90 As nozzle diameter increases, the UTS increases.

For samples with the same percent infill and layer thickness, the UTS was higher for all PLA and ABS samples printed with 0.4 ND compared to 0.3ND. Secondly, analyzing the effect of precentage infill shows that the samples with 70% infill have a comparably higher UTS than those printed at 50% infill. The only time this trend is inconsistent is for the PLA samples printed at 0.3ND. These samples show the opposite trend, and more testing would be required to confirm if this trend is correct. Lastly, one can look at the impact of layer thickness. As seen from figures 1 and 2, about half of the samples show an increase in strength with increase in layer thickness, and half of the samples show a decrease in UTS. This means we cannot conclusively draw a conclusion on the effect of layer thickness from these particular samples, and there was no noticeable trend between the ABS and PLA samples.

RESULTS RASTER ANGLE 45 The Youngs modulus and the Ultimate Tensile Strength was stronger in the PLA than the ABS for samples with the same printing parameters at a print angle of 45. This was the case for all comparable samples except for one.

For both PLA and ABS, as nozzle diameter increases the UTS also increases. This was true for all samples except one, and this discrepancy falls within a normal standard deviation of testing.

Secondly, analyzing the effect of percentage infill shows the samples with 70% infill seem to be comparably stronger than those printed at 50% infill. The only time this trend is inconsistent is for the PLA samples printed at 0.4.ND. However, these samples again are very close and the difference could be accounted for by small errors in testing or data collection. Lastly one can look at the impact of

DISCUSSION Despite the inherent differences in material properties and functions of ABS and PLA it was interesting to observe that they both followed similar trends in response to changing process parameters. From this set of experiments, it seems clear that for specific parameters PLA always seems to have higher tensile strength and Youngs modulus than ABS. Despite this difference in strength, they both share similar trends. Both increase UTS as nozzle diameter increases. They also both increase strength as infill percentage increases. It appears, for the samples printed at 45 degrees, that the strength increases with increased layer thickness.

However, the trend was inconclusive among the samples printed at 0/90 degrees.

However, when looking at these results it is important to remember the scope of this experiment.

Due to time restraints and resources this testing only used one sample at each set of parameters. Testing would be more accurate if there was time to print multiple of the same sample. Additionally it would give a more complete view of the data trends if we could add in more data points to be tested at each parameter. In the future, I would love to continue this work with the opportunity to test more samples and more testing parameters.

REFERENCES 1. Chavan. Review of Effect of Process Parameters on Mechanical Properties of 3D Printed Components, 2017.

2. Fabian. 3D printing Technologies and Materials, 2017 3. Forster. Materials Testing Standards for Additive Manufacturing of Polymer Materials, 2015.

4. Grieser. PLA vs ABS, 2017.

5. Ramon. PLA vs ABS â&#x20AC;&#x201C; the Pros and Cons, 2017.

ACKNOWLEDGEMENTS Research conducted at University of Pittsburgh and National University of Singapore. Funding provided

by Dr. Cui, Swanson School of Engineering, and the Office of Provost.

AC HALL EFFECT MEASUREMENT SYSTEM FOR DEVELOPING EFFICIENT THERMOELECTRIC MATERIALS Louis McLinden, Advisor: Dr. Sangyeop Lee Swanson School of Engineering Laboratory, Department of Mechanical and Material Science Engineering University of Pittsburgh, PA, USA Email: lkm29@pitt.edu , sylee@pitt.edu INTRODUCTION Thermoelectric materials are able to produce an electric potential from a temperature difference.

Thermoelectric materials have the potential to be used for portable refrigeration, waste heat recovery, and solar thermal energy conversion to electricity.

In particular, the waste heat recovery by thermoelectric energy conversion has a potential to significantly reduce the use of fossil fuels and emissions. For example, the thermodynamic efficiency of current internal combustion heat engine is only 30%, which means the remaining 70% of energy is being wasted as heat.

Thermoelectric energy conversion can be used to convert the waste heat into useful electric power.

However, thermoelectric energy conversion has not been widely used due to its poor efficiency of energy conversion. In order to, improve the efficiency, it is critically required to analyze the transport of electrons and holes in thermoelectric materials.

Two important properties related to charge transport are charge carrier density and charge carrier mobility. These two properties can be experimentally characterized by Hall Effect measurement. The Hall Effect is voltage along transverse direction (y-direction) upon electrical current along x-direction, and magnetic field along z-direction. The Lorentz force by the magnetic field make electron (or hole) current asymmetric along ydirection [1].

METHODS Most of the current Hall Effect measurement setup uses DC magnetic field, but this method sometimes causes large error especially for semiconductors with low electron mobility. This can be a serious problem because emerging thermoelectric materials such as conducting polymers exhibit low electron mobility. It is already known that applying AC

magnetic field is very effective in eliminating this error, but it requires additional electronics such as a function generator and Lock-in amplifier to modulate magnetic field and amplify the output Hall effect signal with the modulation frequency [1].

Details of this system are as follows. In between electromagnets, a sample is placed that is connected to a vacuum and temperature controller. The vacuum and temperature controller allow for accurate readings. Attached to these electromagnets is a power supply that delivers an alternating current of which amplitude is temporarily modulated. This alternating current then creates an AC magnetic field with the same frequency as the modulation frequency. The frequency used to modulate the current and magnetic field is 0.1 Hz. The sample is also attached to a Lock-in Amplifier with a current source that reads and stores the values created by the AC magnetic field. The voltmeter is also attached to a Lock-in amplifier. The Lock-in Amplifier is able to separate and amplify the AC signal with a specific frequency from the unwanted DC signal and AC signal with other frequencies.

From the values created by the AC magnetic field, instead of using a traditional lock-in, a program will be run that can read and plot these values on a graph that will eventually create a generated wave function. The purpose of this program is to act as a lock-in amplifier and be able to customize it to store the correct values that fall along the sinusoidal wave and ignore the values that are experimentally incorrect and skew the data.

The voltage and current readings are measured using the van der Pauw method. This method uses a square sample with uniform thickness. Contacts are placed in each of the four corners and are labeled 14 counter clockwise. The way the readings are taken is by applying current from contacts 3 to 1, and

measuring voltage from contacts 4 to 2, and vice versa [2]. This sample would then be labeled R3142.

DATA PROCESSING There are various important hardware devices that make up the AC Hall Effect measurement setup.

These devices measure the temperature, voltage, current, and magnetic field. These readings are then sent to the computer where the program processes their values. Next, the program then calculates the Resistance from the current and voltage readings, takes the Fourier transform of the resistance data.

Here the data is transformed from the time domain to the frequency domain. The purpose of this is to convert the data into a form that will allow easy manipulation and understanding. After performing the Fourier transform on the resistance data, the expected results are a peak in the graph at 0 Hz, and another peak around 0.1 Hz. The peak at 0 Hz represents the DC component of the resistance data, while the 0.1 Hz peak correlates to the modulation of the magnetic field. This resistance data is then filtered using a band-pass filter, to extract the signal that is located at 0.1 Hz. Then, the data is transformed back into the time domain using the inverse Fourier transform. The graph of the inverse Fourier transform is expected to display a sinusoidal wave. Finally, the Hall coefficient can be calculated by multiplying the maximum resistance by sample thickness, and dividing by the maximum magnetic field value. Finally, the thermoelectric material can be analyzed based upon this value.

Figure 1: Fourier Transformed data in frequency domain, showing peaks at 0 Hz and 0.1 Hz.

RESULTS Table (1) shows the required applied currents in order to achieve a certain voltage range to obtain accurate voltage readings. Table (2) displays the calculated Hall coefficient values based upon the raw resistance data. These values do not come from the data that has been transformed and filtered.

DISCUSSION Although due to time constraints, the end results of this experiment have not been concluded. One of the major goals of this experiment was to learn a new programming language to then develop a program that can be customized to act and perform the operations of a traditional Lock-in amplifier.

After having many successes with the program, when it came to the final step of filtering the data, the program came up short. The filters that needed to be applied include a digital filter with synchronous filtering capabilities, two notch filters, and an anti-aliasing filter. As a result of this shortcoming, a traditional lock-in amplifier would need to be used in order to apply these filters.

REFERENCES [1] J. R. Lindemuth. An Introduction to AC Field Hall Effect Measurements.

[2] Appendix A Hall Effect Measurement. 7600 Series Hall System Hardware Reference Manual.

[3] About Lock-In Amplifiers. Stanford Research Systems.

ACKNOWLEDGEMENTS The PPG foundation for providing the grant, Professor Lee for being a great mentor, and all the students in the lab.

Figure 2: Hall Effect Setup

Desired Voltage Range Configuration R3142 applied current Configuration R4213 applied current

100ÂľV 35mA 40mA

200ÂľV 60mA 75mA

Table 1: Desired Voltage Range and Applied Current

Configuration Raw Hall coeff

R3142 w/ 35 mA 3.129E-7 m^3/C

Table 2: Raw Hall Coefficient values

R3142 w/ 60 mA 2.235E-7 m^3/C

R4213 w/ 40 mA 2.682E-7 m^3/C

R4213 w/ 75 mA 2.235E-7 m^3/C

INTEGRATING FUNCTIONAL ELECTRICAL STIMULATION CONTROL AND IMUBASED LIMB ANGLE ESTIMATION FOR DROP FOOT CORRECTION Levi S. Burner and Dr. Nitin Sharma Sharma Lab, Department of Mechanical Engineering University of Pittsburgh, PA, USA Email: lsb27@pitt.edu, Web: http://www.engineering.pitt.edu/Labs/SHARMA/ INTRODUCTION Over 800,000 strokes are reported annually and a common side effect of stroke is drop foot, which causes a foot to drag or slap on the floor during walking (swing phase). The condition is due to the inability to control ankle muscles that produce dorsiflexion. It affects a patientâ&#x20AC;&#x2122;s ability to balance and walk at a steady pace. The loss of control also increases the risk of fall from tripping [1].

Current solutions include using single channel Functional Electrical Stimulation (FES) and a ground contact sensor. When the ground contact sensor detects the foot has lifted off the ground, the FES system activates and stimulates the peroneal nerve (to elicit dorsiflexion) so that the foot rises and clears the ground. Another sensing solution is to use electromyography to predict gait posture of a subject and apply stimulation to the peroneal nerve at an appropriate time [2].

The goal of this research is to develop a wearable real-time foot drop correction system that can be attached to an individual. It uses inertial measurement units (IMUs) attached to the thigh, shank, and foot for predicting limb angles during gait. It also has a method to apply FES using a commercial stimulator. The motivation for a multiple IMU system is to obtain more comprehensive sensory information on limb postures and thus the ability to provide multichannel FES. Compared to existing single channel drop-foot systems, this will facilitate a high fidelity multi-channel control of multiple muscles that govern gait.

METHODS Three primary subsystems were designed. The IMU data collection system (IMU Mux), the Control Software, and the FES system. In Figure 1 the overall system architecture is illustrated.

The low-cost Invensense MPU9250 was used. It supports sampling of the gyroscope and accelerometer at 1 kHz and is available on a highquality board from Sparkfun. Testing verified that a single 2 MHz Serial Peripheral Interface (SPI) bus could support a 1 kHz sample rate of 6 IMUs.

Figure 1: High-level overview of the control system.

Signal integrity was a concern because SPI is designed for use with lines several centimeters long.

In this case, the distance from the IMU Mux to an IMU could be a meter. Category 5 (Cat5) cabling is used for the SPI bus lines. It helps minimize crosstalk between signal lines. The IMUs share bus lines by being connected in series. This reduces the capacitance of the signal lines compared to the capacitance due to running separate cables. To reduce overshoot and prevent reflections, source termination is used on all SPI bus driver outputs.

The Sparkfun MPU9250 breakout boards and Cat5 jacks are mounted on a custom PCB. The board is mounted in a 3D printed case that includes a slot for a Velcro strap. The strap is used to attach the case to a subject.

The IMU Mux uses a Teensy 3.2 for the SPI communications and relaying data over USB. It is mounted on a custom PCB that is mounted directly to the computer running the control software. A Raspberry Pi 3 is used to run the control software.

The Pi, IMU Mux, and IMUs are powered from a rechargeable 2 cell, 1 Ah Lithium Polymer battery.

The Pi, IMU Mux, and battery are enclosed in a 3D printed case.

To apply FES a Hasomed RehaStim v1 was used. It includes its own battery power.

Since this system is designed for use with future research, it was decided that a simple toolbelt was sufficient for holding the system. A picture of a subject wearing the system can be seen in Figure 2.

Figure 2: Control computer, IMU Mux, FES unit, and IMUs attached to a human.

DATA PROCESSING To verify the signal integrity in the SPI communication lines an oscilloscope was attached to the data input lines of the IMUs as well as the data input lines of the IMU Mux. The signals were observed while the maximum supported length of Cat5 cabling was attached between each IMU. The IMU data was sent from the control processor to a powerful PC using WiFi. To estimate the IMUs orientations, six axis fusion was performed using a Python implementation of the Madgwick sensor fusion algorithm [3]. The joint angles were extracted from the orientations and displayed in a skeletal model in real time. The data was also logged to a file.

The output of the FES unit was attached to an oscilloscope and amplitude and frequency commands were sent from the Raspberry Pi. RESULTS The oscilloscope measurements from the SPI bus revealed that overshoot, reflections, and crosstalk were within acceptable levels.

Voltage measurements from the output of the FES unit verified the Raspberry Pi can control the output of the FES unit.

The toolbelt was observed to not cause discomfort.

However, the IMUs required frequent adjustment.

Using the joint angle extraction and visualization software it was verified that the skeletal model depicted the movements of the subjectâ&#x20AC;&#x2122;s legs. The data during a full step of the right leg was graphed and can be seen in Figure 3.

Figure 3: Joint angles versus time during a full step of the right leg.

DISCUSSION It was demonstrated that the sensors used could produce data required for limb angle estimation.

Further work needs to be done to improve the algorithms and optimize them so they can be run on the Raspberry Pi in real time.

Additionally, the experiment verified that the processing unit and the Stimulator could be mounted to a human subject while remaining reasonably comfortable. However, further work needs to be done to improve the mounting of the IMUâ&#x20AC;&#x2122;s. They would frequently shift during usage causing inaccurate measurements.

REFERENCES 1. O'Dell et al. Phys Med Rehabil Clin N Am 6(7), 587-601, 2015.

2. Dutta et al. EURASIP J Adv Signal Process 2012, 153, 2012.

3. Madgwick. Report x-io and University of Bristol, 25, 2010.

ACKNOWLEDGEMENTS Funding was provided by the Swanson School of Engineering and the Office of the Provost.

PROCESS OF INSERTING OPTIMIZED LATTICE STRUCTURE FOR SELECTIVE LASER SINTERING Shawn J. Hinnebusch ANSYS Additive Manufacturing Research Laboratory, Department of Mechanical Engineering & Material Science University of Pittsburgh, PA, USA Email: sjh68@pitt.edu INTRODUCTION The goal of this project was to use cellular structures to light weight an additive part. Reduction in mass cuts the building time needed for production, which makes additive manufacturing (AM) a more competitive option. In addition to reduced cost, AM can have more complex shapes manufactured allowing for additional changes that could not be manufactured before with traditional casting and machining methods.

METHODS The first step in optimizing the part was establishing a loading condition in ANSYS to simulate the forces on the faces that have an applied load. Once the optimization was completed, another set of Finite Element Analysis (FEA) was completed to confirm the optimization. The lattice structure topology optimization software developed by Dr. Albert Toâ&#x20AC;&#x2122;s group at University of Pittsburgh software was used to optimize this part. [1] Figure 1 shows an example of an optimized bracket.

Oftentimes, a part cannot have a lattice throughout the entire area. In this example, the round cylinder is completely solid along the section that connects the bracket to the wall for maximum strength. Lattice was only inserted into the solid portion between the wall mount and the cylinder. To complete this, the part was optimized, then split into three-sections using SpaceClaim.

Figure 1: Optimized Bracket with variable density lattice

By changing the unit size of a lattice, it was found that many small cells could not be inserted into a complex shape due to software limitations. A size of four to five-millimeter unit cube lattice was found to be the easiest to insert and cut. It took many iterations to find a combination that would successfully combine.

Many times, complex shapes cannot be completely meshed due to difficulties in cutting the lattice, combining it, and performing FEA. Throughout the summer, Solidworks, AutoDesk Inventor, and SpaceClaim were used to cut, combine, and modify these structures. Once the lattice was generated, it was trimmed to the size of the part. Then the part was shelled to a size of one millimeter that was inserted and combined with the optimized lattice structure.

As accurate FEA models were difficult to predict the stresses after optimization, the plan was to print multiple designs and complete testing to confirm results. Since printing parts and testing were expensive, more time was spent to reduce the number of designs. To accomplish this, a uniform lattice was created to allow for a mesh to work in ANSYS. As this was done, other types of meshing in ANSYS could be used; however, obtaining convergence of the stresses with decreasing element size failed, as the stress hit a singularity point at the sharp joints inside the lattice. The only way to fix the singularities was to add fillets to the joints of the lattice. This was the next step to make a uniform lattice with fillets to be inserted into a complex part. This proved to be difficult to cut a lattice with fillets and combine with an outside shell to provide a smooth surface. After many attempts, a filleted uniform mesh was successfully inserted, but the convergence analysis still failed at the intersection between the lattice and shell. Figure 2 shows how sharp edges can be created when a lattice is cut. Trying to combine this sharp edge with a shell causes many errors.

Figure 2: Problem area of cutting lattice (indicated by arrow)

DATA PROCESSING Many iterations of lattices were created to find an FEA model that produced accurate results. Fillets of 0.1 mm were added to the uniform lattice in the analysis. Notice in Figure 3 that there is a significant decrease in stress as the fillet size increases. The orange line shows a decrease in stress from the previous fillet size, but as fillet size increases so does the total mass. The blue line shows the percent increase of mass from each iteration. The largest stress decrease is between 0.1-0.5 mm fillets. After this point, the mass starts to increase at a much faster rate. Because of the computing power needed to produce results of 0.8+ mm fillets and the slight decrease in stress, these results were left out. Fillets of 0.5 mm greatly reduce the stress, but also allow for easier processing of the graphics and solving, thus reducing the time required to setup and solve.

find the accuracy of this mesh compared to the mesh that reached convergence, a uniform cubic lattice was tested using a convergence mesh and a tetrahedral patch independent mesh. It was found that the stress could be estimated within 10%, allowing designs to be narrowed down. For this test, a fiveunit cell cube was used. A fillet size of 0.1 mm was added for the stress convergence analysis while no fillet was added to the patch independent. By using this approach, less printing, machine finish, and testing will need to be completed.

DISCUSSION By adding optimized cellular lattice structures, AM parts are more marketable as the cost is reduced and the functionality of the part can be improved. In order to design a lattice structure incorporated in a part, FEA is critical to narrow down designs instead of testing numerous designs to assure they pass the requirements. Now only four tests need to be conducted. Future goals will consist of printing parts for testing to compare with the predicted FEA results.

REFERENCES [1] A. C. To, Lin Cheng, Jiaxi Bai, Emre Biyikli, and Pu Zhang, Lattice Structure Design Optimization for Additive Manufacturing, [Computer Software], University of Pittsburgh, 2015.

[2] A.O., Aremu, I. Maskery, C. Tuck, I. A., Ashcroft, R.D., Wildman, and R.I.M, Hague. “A Comparative Finite Element Study of Cubic unit Cells for Selective Laser Melting” (2014).

[3] Lin Cheng, Pu Zhang, Emre Biyikli, Jiaxi Bai, Joshua Robbins, and Albert C. To. “Efficient Design Optimization of Variable-Density Cellular Structures for Additive Manufacturing: Theory and Experimental Validation” (2017).

Figure 3: Percent change in each iteration of mass vs stress

[4] Erik Andreassen, Anders Clausen, Mattias Schevenels, Boyan S. Lazarov, Ole Sigmund.

“Efficient Topology Optimization in MATLAB Using 88 Lines of Code” (2011).

RESULTS By using the topology optimization software, many designs were created and narrowed down to four.

This was done by using ANSYS tetrahedral patch independent meshing to estimate the stress levels. To

ACKNOWLEDGEMENTS Joint funding was provided by Swanson School of Engineering and the Office of the Provost. I would also like to thank Dr. Albert To and Kennametal for their support.

The Physiological Role of Mitochondrial Amidoxime Reducing Component 2 Jimmy Zhang, Courtney E Sparacino-Watkins and Mark T Gladwin Vascular Medicine Institute, Department of Medicine University of Pittsburgh, PA, USA Email: jiz127@pitt.edu, Web: http://vmi.pitt.edu/ INTRODUCTION Mitochondrial Amidoxime Reducing Component 2 (mARC-2) is a novel molybdenumcontaining enzyme found in most eukaryotic organisms, including humans [1]. The mARC-2 enzyme is an oxidoreductase which metabolizes a broad range of substrate (e.g., N-hydroxylated amidoxime compounds [2] and nitrite [3]). Still, the physiological function of mARC-2 is unknown.

While the exact function of mARC-2 is not clear, studies have suggested a role in lipid metabolism [4, 5]. Interestingly, the mARC-2 knock out (KO) mice, which do not express the protein, revealed decreased body weight phenotype. Our lab has recently established that mARC-2 KO in moderately aged (10-month-old) male mice maintained on a normal chow diet had reduction in body weight and fat mass, lower glucose and insulin levels, with increased feeding, activity, and energy expenditure. Based on the observed phenotype in mice and high expression of mARC-2 in liver hepatocytes [5, 6], we hypothesize that mARC-2 functions in lipid homeostasis (for example, the export and usage of fatty acids) in the liver. To test this hypothesis, we are tested the effect of mARC-2 KO in mice feed a high fat diet on body weight and liver lipid accumulation. Additionally, we looked at the effect of high fat diet on mARC-2 expression in the mouse liver.

METHODS Randomly selected male mouse littermates were provided either a high-fat diet (HFD) or lowfat diet (LFD) at 9 weeks old. Twenty-four mice were provided a HFD containing 60% kcal energy from fat. Twelve mice were given LFD that contained 10% kcal energy from chow. Of the 36 male C57/BL6N strain mice, 16 were complete KO, 12 were heterozygotes (HET), and 8 were wildtype (WT). Body weights were recorded weekly. All animal experiments were conducted in accordance with institutional animal care procedures at the University of Pittsburgh.

Protein and transcript were extracted from mouse liver tissue that was flash frozen in liquid nitrogen using standard techniques. Mouse liver tissue was harvested from C57/BL6 or AKR male mice maintained on a HFD or LFD. A total of 12 animals were tested, with 3 animals per group. Tissue was disrupted in the Protein Extraction Reagent with Halt protease inhibitor cocktail (ThermoFisher).

Protein concentration was measured using a BCA protein assay prior to protein electrophoresis and western blot (WB). An anti-tubulin antibody was used as a loading control and an anti-mARC-2 antibody (Sigma, Human Protein Atlas) specific for mARC-2 (i.e., no reactivity to mARC-1). Tublin and mARC-2 expression were visualized using chemiluminescence (ThermoFisher) and a digital chemiluminescence detector (BioRad).

RNA extraction was accomplished using the RNeasy Plus Mini Kit quick-start protocol (Qiagen). Spectrophotometry was used to measure RNA content prior to quantitative Real-Time Polymerase Chain Reaction (qRT-PCR).

Commercially available Taqmen primers specific for mouse mARC-2 and glyceraldehyde 3phosphate dehydrogenase (GAPDH) were used.

GAPDH was used as an internal control and a means of normalization.

DATA PROCESSING Plotting and statistical analysis of the mouse body weights over time in the HFD trial were performed with GraphPad Prism 7 software.

Western Blot analysis was carried out on ImageJ and normalized to the internal control. Significance was measured using Student t-test. The qPCR data was processed in Microsoft Excel 2010, and relative expression levels are defined by the cycle threshold.

All error bars indicate standard deviation RESULTS The mARC-2 KO mice on maintained on LFD have lower body weights than both WT and HET littermates (Figure 1). Similarly, the mARC-2 KO mice provided a HFD maintain a lower body

HFD trial

no changes in transcript levels. This is consistent with published studies which found that HFD modulates mARC-2 protein expression, but not transcript levels, in C57/BL6W mice [7]. However, this trend did not carry over to AKR mouse strain, although these data did have a relatively large standard deviation and small sample size. Another possible explanation is this observation in mice is strain specific. Interestingly, we found that mARC2 protein and transcript levels are much higher in the AKR strain, which is more susceptible to dietinduced obesity.

Figure 1. Mouse weights of ongoing mouse trial comparing high-fat diet (HFD) and low-fat diet (LFD) of male mice with different mARC2 genotypes (wildtype, WT; heterozygous, HET; knock out, KO).

Special diets were started at 9 weeks old.

weight than WT and HET littermates. Also, KO mice on a HFD weight more than those on a LFD. The mARC-2 transcript levels measured by qRT-PCR (Figure 2A) found no significant differences associated with diet (HFD vs. LFD) in either C57/BL6 or AKR mouse strain. However, differences among the strains, independent of diet, is clearly evident. Protein analysis by western blot (Figure 2B) revealed some increase in mARC-2 protein levels in the C57/BL6 strain, but not the AKR strain.

DISCUSSION While our study and others have suggested that mARC-2 functions in lipid homeostasis, the exact mechanism is unclear. Elucidating the role of mARC-2 in lipid metabolism could have important implications in obesity, diabetes, or fatty liver diseases. The goal of this study was to determine if mARC-2 KO was protective against diet induced obesity. We used the well-established HFD mouse model of diet-induce obesity and the mARC-2 KO mice. We show that deleting mARC-2 is protective against diet induced obesity. While the mARC-2 KO mice do gain weight on the HFD, compared to LFD, but this is less than HET or WT on the HFD. Additionally, we determined the effect of HFD on mARC-2 transcript and protein levels in livers of mice provided a HFD. We tested two strains of mice, C57/BL6 and AKR. While both strains are susceptible to diet-induced obesity, it has been shown that the AKR strain is more susceptible [8]. Figure 2 shows an up-regulation of mARC-2 protein levels in the HFD feed C57/BL6 mice, but

Figure 1. mARC-2 transcript levels measured by qRT-PCR (A) and mARC-2 protein levels measured by western blot (B). Samples are from mouse liver extracts. Each experimental group had a sample size of three.

REFERENCES 1. Ott, G., A. Havemeyer, and B. Clement, The mammalian molybdenum enzymes of mARC. JBIC Journal of Biological Inorganic Chemistry, 2015. 20(2): p. 265-275.

2. Krompholz, N., et al., The mitochondrial amidoxime reducing component (mARC) is involved in detoxification of Nhydroxylated base analogues. Chemical research in toxicology, 2012. 25(11): p. 2443-2450.

3. Sparacino-Watkins, C.E., et al., Nitrite reductase and NO synthase activity of the mitochondrial molybdopterin enzymes mARC1 and mARC2. Journal of Biological Chemistry, 2014.

4. Neve, E.P.A., et al., Amidoxime Reductase System Containing Cytochrome b5 Type B (CYB5B) and MOSC2 Is of Importance for Lipid Synthesis in Adipocyte Mitochondria. Journal of Biological Chemistry, 2012. 287(9): p. 6307-6317.

5. Neve, E.P., et al., Expression and Function of mARC: Roles in Lipogenesis and Metabolic Activation of Ximelagatran. PloS one, 2015. 10(9): p. e0138487.

6. Su, A.I., et al., A gene atlas of the mouse and human proteinencoding transcriptomes. Proceedings of the National Academy of Sciences of the United States of America, 2004. 101(16): p.

6062-6067.

7. Jakobs, H.H., et al., The N-Reductive System Composed of Mitochondrial Amidoxime Reducing Component (mARC), Cytochrome b5 (CYB5B) and Cytochrome b5 Reductase (CYB5R) Is Regulated by Fasting and High Fat Diet in Mice. PLoS ONE, 2014. 9(8): p. e105371.

8. Alexander, J., et al., Distinct phenotypes of obesity-prone AKR/J, DBA2J and C57BL/6J mice compared to control strains.

International Journal of Obesity, 2006.

ACKNOWLEDGEMENT We are grateful to Yen-Chun Lai, PhD for providing us with the samples used for Western Blot and qPCR.

COMPUTATIONAL AND EXPERIMENTAL MODELING OF CYTOCHROME B5 REDUCTASE DYNAMICS Alyssa Bell, Adam Straub, Ph.D. and Patrick Thibodeau, Ph.D. Thibodeau Lab, Department of Microbiology and Molecular Genetics University of Pittsburgh, PA, USA Email: abell@pitt.edu INTRODUCTION The human cytochrome enzymes play critical roles in maintaining healthy respiration by aiding in electron transport and oxidation-reduction reactions with the use of iron-containing haem groups as catalysts. These reactions are partially regulated by accessory enzymes, including multiple reductase proteins. Among these, the cytochrome B5 reductase (CyB5R3) is critical for the conversion of methaemoglobin to haemoglobin and participates in multiple metabolic pathways [1].

Recent clinical and animal studies conducted at the University of Pittsburgh demonstrate that mutations in the human cytochrome B5 reductase result in an elevated risk of hypertension and a significant increase in mortality due to cardiac failure. A single mutation, a conservative substitution of a threonine to a serine (T117S), is correlated with elevated hypertension and cardiovascular disease and is prevalent in 23% of the African-American population in the United States [2].

While mutations in CyB5R have been identified in patients, their impact on the structure and function of this enzyme is not established. Moreover, the location and conservative nature of the T117S mutation provides few clues regarding the changes in CyB5R3 structure and function. Preliminary thermodynamic data suggests that the T117S variant is destabilized when compared to the wildtype (WT) CyB5R3 protein. Understanding the physical basis of CyB5R3 dysfunction and the T117S mutation will increase our understanding of the molecular pathologies and aid in therapeutic development.

HYPOTHESIS We hypothesized that T117S decreases the thermodynamic stability and increases native-state dynamics of CyB5R3 by altering FAD binding, which is critical for enzymatic function and serves as a structural co-factor in the folded protein.

METHODS Molecular dynamics: The effects of the T117S mutation on the structural dynamics of the CyB5R3 protein were modeled using computational tools.

The Senderowitz laboratory at Bar Ilan University in Tel Aviv ran 100 ns, all-atom simulations on WT CyB5R3 and the T117S mutant to identify changes in protein dynamics using GROMACS [3].

Protein expression and purification: Structural models in the RCSB Protein Data Bank (PDB: 1UMK) suggested that the T117S mutation could be accommodated in the native CyB5R3 structure.

PCR-based mutagenesis was performed to generate the T117S variant. The WT and mutant proteins were expressed in E. coli and purified using standard protein chromatographic separation on an AKTA FPLC using Ni-NTA and S300 columns.

In vitro characterization: Thermodynamic stability of the purified CyB5R proteins was assessed with the previously established ThermoFluor Protein Assay [4]. Protein unfolding is monitored by SYPRO Orange dye fluorescence, which increases as the dye binds to exposed hydrophobic regions of the denaturing protein. In parallel, FAD release was also evaluated by fluorescence to evaluate changes in nucleotide binding and protein denaturation.

DATA PROCESSING The molecular dynamics trajectories generated in the Senderowitz laboratory were assessed to quantitatively determine distances between any two atoms in both WT and the T117S mutant through Matlab scripting. Mean distances between atom pairs and root mean standard fluctuations were calculated for specific atom pairs in the MD trajectories.

Thermodynamic stability calculated from the raw fluorescence traces generated in ThermoFluor experiments. The traces were normalized and the mid-point of the fluorescence transition (Tm) was calculated using sigmoidal regression, assuming a

two-state unfolding model.

Regression was accomplished using GraphPad Prism IC50 and SimpleDSF Viewer [5].

RESULTS Analysis of the molecular dynamics data suggests that the mutant CyB5R3 exhibits increased dynamics when compared to WT when specific atom pairs were analyzed. Local CyB5R3 dynamics were assessed by measuring the distance between the T117/T117S site and neighboring secondary structure elements. Global changes in CyB5R3 structure were assessed by evaluating the dynamics of a highly-conserved salt bridge distal to the T117 locus. Through three MD simulations, the average distance between the T117 loop and the central αhelix was marginally greater for WT than T117S (Table 1). Similarly, the mean distance across the conserved salt bridge was greater for WT than the mutant. Both of these results suggested that the structure was subtly altered by the T117S substitution.

Salt Bridge Dist. (Aº)

T117/α Helix Dist. (Aº)

WT

T117S

WT

T117S

5.5 ± 1.2 5.6 ± 1.4 4.7 ± 1.2

4.0 ± 1.0 4.4 ± 1.3 4.6 ± 0.4

18.0 ± 0.9 18.1 ± 0.9 18.1 ± 1.1

17.2 ± 0.8 17.5 ± 1.0 17.5 ± 0.7

Table 1: Mean distances and standard deviations determined from MD simulations.

Thermofluor stability measurements showed a destabilization of CyB5R3 with the T117S mutation by about 2ºC, due to early protein unfolding and FAD release. Supplementing the Thermofluor reactions with FAD also stabilizes both the T117S and WT proteins, suggesting that FAD is a stabilizing cofactor.

After finding that the release of FAD is associated with protein unfolding, we began small molecule screens to identify molecules that might stabilize FAD-bound CyB5R3. A small pilot screen with 320 compounds was performed using the ThermoFluor Assay. Analyses of these binding experiments suggest that this approach could be further optimized to identify small molecule stabilizers for the T117S CyB5R3 mutant (Figure 1).

DISCUSSION While the T117S mutation has been identified in patients, its structural and functional impact has not

Figure 1. Waterfall plot generated from small molecule screen of CyB5R3 T117S.

been fully established. Characterizing CyB5R3 through solution based analyses, including thermodynamic and structural studies, provides a holistic understanding of the T117S mutation, thus aiding in therapeutic development.

Since the structural models and molecular dynamics data show that the T117S variant exhibits altered protein dynamics, small molecule binding might be a potential therapeutic strategy to revert the changes in proteins conformation.

Ongoing studies are focused on further characterizing the differences in biochemical behavior of the WT and T117S CyB5R3 proteins and understanding the structural and energetic contributions of the conserved salt bridge.

REFERENCES 1. Straub et al. Redox Biology, 405-410, 2013.

2. Prchal et al. Human Genetics 99, 248-250, 1997.

3. Senderowitz. Unpublished Data and Personal Communication.

4. Ericsson et al. Analytical Biochemistry 357, 289-298, 2006.

5. Fernig et al. Peer J, 2015.

ACKNOWLEDGEMENTS This research was funded by the Swanson School of Engineering and the Office of the Provost. Molecular Dynamics data was performed in the Senderowitz Lab in the Department of Chemistry at Bar Ilan University. Parallel in vivo studies were performed in the Straub Lab in the University of Pittsburgh Department of Pharmacology and Chemical Biology and the Vascular Medicine Institute.

Examination of Two Tet-On Constructs with Sh95 in the Visual Cortex Nowa B. Bronner and Oliver M. Schluter Department of Neuroscience University of Pittsburgh, PA, USA Email: nbb8@pitt.edu, Web: http://cnup.neurobio.pitt.edu/people/peopleDetail.aspx?uid=739 INTRODUCTION One of the focuses of the Schluter laboratory is determining the role of postsynaptic density protein95 (PSD-95) in long-term synaptic plasticity during physiological and pathological learning. A greater understanding of the functions of proteins in neurons will lead to the illumination of the causes of neurodevelopmental disorders, and eventually aid in finding a cure for such disorders. In past experiments, the PSD-95 gene was knocked out using homologous recombination in mice to examine the effect of PSD-95. This process works well in altering genes, but it limits the scope of experiments on PSD-95 because only one type of mutation is generated at a time and the generation of mutant mice is comparably slow. More information about the role of PSD-95 could be obtained if gene expression could be turned on and off.

Over the years, an inducible gene expression system has been developed using tetracycline switches from bacteria [1]. Two complementary systems were made: Tet-On and Tet-Off. These druginducible gene expression systems can be combined with RNA interference (RNAi) to posttranscriptionally silence a gene of interest. Both the Tet system and shRNA can be incorporated into recombinant adenoassociated viral vectors (rAAV) [2], which can transduce neurons to express the recombinant constructs. Unlike the LoxP and Cre system, the Tet-On system is not guaranteed to work. Before the Tet-On system combined with PSD-95 can be used in behavioral experiments, the effectiveness must be examined.

METHODS Construct B was made through standard molecular cloning technique. DNA sequencing was conducted to confirm the sequence. Stereotactic P0 injections of construct A, construct B, and a positive control were conducted on NexCre knockdown and wildtype C57BL/6 mice in the visual cortex. The

pups were anesthetized with ice and injected in 4 different spots in the visual cortex at various depths.

After the developmental stage, some mice were placed on the doxycycline diet to turn on the tetracycline sensitive element. Subsequently, injected mice brains were imaged for fluorescence.

The brain slices were fixed, stained with DAPI, and mounted on slides. They were imaged with GFP, dsRed filters on the stereomicroscope. On the confocal microscope, they were imaged with DAPI and GFP filters. The percent area affected by the virus and the percent neurons transduced were approximated from the images. A western blot was performed to measure the amount of expressed PSD-95. 8 punches from the brightest fluorescing spot were taken as samples. All steps were conducted using standard protocol from the Schluter Laboratory.

DATA PROCESSING The data from the western blot was collected using Image Studio. With that data, a one tailed t-test with unequal variance was conducted on excel. The approximation of the transfected area was conducted on the image with the greatest amount of fluorescence for each construct.

RESULTS In this study, we tested two Tet-on constructs: construct A and construct B. Construct A is Cre activated while construct B is not. Because construct A is Cre activated, it had to be injected with Cre or into NexCre mice. Injecting into NexCre mice specifies transduction in glutamatergic neurons. Construct B also has a pause site that should limit cross talk between the two promoters included in the plasmid. Construct A and B both have a Tet element paired with GFP driven by a neuron preferential promoter and a red fluorescence protein paired with sh95 driven by the TRE promoter. A transduced neuron would show

green fluorescence. The Tet element, in the presence of doxycycline, turns on the TRE promoter.

Consequently, the red fluorescence is expressed and PSD-95 is suppressed by the sh95. The positive control has no Tet element, expressing sh95 and GFP only. All constructs are made with adenoassociated virus serotype 8 (AAV8).

Figure 1 below has 4 images with the brightest fluorescence with GFP for each specific type of injection.

Figure 1: Top left image is the positive control shot at .5 second exposure. Top right is construct A injected in a NexCre mouse at 2 second exposure. Bottom left is construct B injected in a wildtype mouse at 2 second exposure. Bottom right is construct A injected with Cre into a wildtype mouse with automatic exposure. Top left, top right, bottom left shot at 1.6x, and bottom right shot at 1.25x.

The positive control has the brightest fluorescence, covering 86% of the cortex and hippocampus.

Construct A injected into the NexCre mouse has dimmer fluorescence covering 14% of the cortex and hippocampus. Construct B injected into wildtype mice showed minimal fluorescence, covering 5% of the cortex and hippocampus, and construct A injected with Cre in wildtype mice showed no fluorescence. Many images showed the fluorescence in the hippocampus rather than the cortex. Images taken with the dsRed filter of mice that have been on the doxycycline diet for 14 days and expressed GFP showed no red fluorescence, indicating the Tet system did not work efficiently.

Examination of the positive control with the confocal microscope revealed a 94% transduction rate at the location with the most fluorescence. At the brightest location under 63x magnification, there were 70 neurons fluorescing DAPI and 66 neurons fluorescing GFP. To test for knock-down

efficiency in the positive control, we quantified protein levels from slices with the brightest fluorescence spot with western blotting. The t-test on the data from the western blot resulted in a pvalue of .064 from a sample size of 4.

DISCUSSION The fluorescence of the two test constructs were too light and did not affect enough area to be effective in behavioral tests. There was not enough fluorescence for it to be worthwhile to conduct a western blot or to examine the samples under the confocal microscope. A bright fluorescence as seen in the positive control is desired. A reason for this disparity may be the different promoters used between the constructs. The positive control incorporates a CAG promoter that works well.

However, the CAG promoter is large and lacks specificity in the cells it is induced by.

Neither of the Tet-On constructs showed red fluorescence. It is difficult to conclude that the TetOn system did not work because the GFP fluorescence was so sparse. Before we can experiment with the doxycycline, we need to have a higher transfection rate of the virus. We would suggest experimenting with different promoters.

One test could be incorporating the promoters from the test constructs into the positive control construct.

It is also possible to try the CAG promoter in construct B due to its smaller size. The western blot result suggests that there is a difference in PSD-95 expression between the knockdown and the wildtype. However, the t-test reveals that there is not a significant difference. This could be due to the small sample size. We would suggest doing the experiment with a larger sample size.

REFERENCES 1. Gossen and Bujard. PNAS 89, 5547-5551, 1992.

2. Samulski et al. J Virology 63, 3822-3888, 1989.

ACKNOWLEDGEMENTS I would like to thank Dr. Huang for guiding me through procedures and the Swanson School of Engineering and the Office of the Provost for the award to work on this research.

Thermoresponsive NIPAAm-Based Gel for Targeted Delivery to the Retina Nathaniel Myers and Michael Washington Fedorchak Lab, Department of Ophthalmology University of Pittsburgh, PA, USA Email: nate.myers@pitt.edu, Web: http://www.fedorchaklab.com/ INTRODUCTION Synthesis of poly(N-isopropylacrylamide) (pNIPAAm) non-degradable gel scaffolds for controlled delivery has been increasingly studied in recent years due to their desirable thermoresponsive phase behavior [1,2]. The thermoresponsive nature of the pNIPAAm gels allows for a liquid injection at room temperature, followed by gelation when exposed to physiological conditions. Fields such as orthopedic engineering and regenerative medicine have utilized pNIPAAm for applications such as bone scaffolds and targeted delivery of gene therapies [1,3]. Consequently, further novel biomedical applications in applications such as drug delivery, cell immobilization, and tissue engineering have been generated, validated, and implemented [1,4]. Poly(NIPAAm) is especially useful due to its lower critical solution temperature (LCST) of 32 °C, which is slightly lower than that of physiological temperature (i.e. 37 °C). The LCST is defined as temperature at which the polymer transitions from a soluble to insoluble state within an aqueous environment, which is both enthalpically and entropically driven by hydrogen bonding.

Manipulating the LCST of pNIPAAm is traditionally done by altering the hydrophobicity or hydrophilicity of the polymer through the addition of comonomers.

Copolymerization with other monomers and crosslinking agents can lead to further specializations of the gel including the incorporation of modifiable functional groups, increases in mechanical properties, and dual-responsive properties [2,4].

We hypothesized that pNIPAAm would serve as an ideal candidate for intraocular gene delivery applications involving viral vectors. However, the non-degradable nature of pNIPAAm would result in its persistence within the eye. Sheardown et al and Vernon et al have prepared degradable NIPAAm based copolymers through the incorporation of hydrophilic (i.e. acrylic acid (AA)) and degradable (i.e. acryloyloxy dimethyl-γ-butyrolactone (DBA))

comonomers, which have been utilized for various drug delivery applications [3,6]. These copolymers have been shown to be fully exported and processed by the kidney in small amounts before becoming cytotoxic to surrounding environments [5,6]. We hypothesize that the incorporation of a hydrophilic and modifiable comonomer, 2-hydroxypropyl methylacrylamide (HPMA), will offer similar LCST behavior as the NIPAAm-AA-DBA systems.

The primary aims of this study include the synthesis and characterization of a novel degradable thermoresponsive pNIPAAm-based gel matrix for viral vector drug delivery applications, Scheme 1.

Incorporation of degradable (i.e. DBA) and modifiable (i.e. HPMA) comonomers, are hypothesized to provide a desired degradation profile (<5 d) and coupling sites for post-polymerization modifications.

Scheme 1: (A) Synthesis of thermoresponsive, degradable, and modifiable gel and (B) proposed degradation products at physiological conditions.

METHODS All materials were reagent grade and obtained from Sigma Aldrich unless otherwise noted.

Poly(NIPAAm-co-DBA-co-HMPA) copolymers were synthesized via free radical polymerization using the co-monomer feed ratios of 88.4 mol% NIPAAm, 5.6 mol% DBA, and 6.0 mol% HPMA. The redox pair of ammonium persulfate (APS) and N,N,N’,N’-tetramethylethylenediamine (TEMED)

Gelation time was determined by introducing 1 mL of 4 °C copolymer into a 44 °C water bath. A stopwatch was used to measure the total time from application to the completed phase transition. The full gelation process was then documented by removing the copolymer from the water bath after 2 minutes and placing the precipitated polymer back into the refrigerator to re-solubilize the poly(NIPAAm-co-DBA-co-HPMA) chains.

LCST measurements were gathered in triplicate using SpectraMax M4 UV-Vis spectrophotometer at 415 nm. Absorbance values were recorded in 1 °C increments in the temperature range spanning 35 °C to 50 °C. The microstructural composition of the poly(NIPAAm-co-DBA-co-HPMA) gel was validated using a 500 MHz Bruker Avance III 1HNMR spectrometer with D2O as the reference solvent.

RESULTS AND DICUSSION The molar composition of the poly(NIPAAm-coDBA-co-HPMA) gel was determined to be 91.4 mol% NIPAAm, 1.4 mol% DBA, and 7.2 mol% HPMA by 1H-NMR. The gelation time was found to be 2 minutes at 44 °C, suggesting the gel would not precipitate during the injection portion of a vitrial injection procedure, Fig 1. However, as the gel would not precipitate at 37 °C, an additional monomeric subunit such as acrylic acid must be incorporated in the future to lower the LCST of the copolymer to just below physiological conditions.

Figure 1: Gelation process (a) 1 day after in 4 °C refrigerator, (b) 15 seconds after in 44 °C water bath, (c) 2 minutes after in 44 °C water bath and (d) 2 min removed from water bath in 4 °C refrigerator

The absorbance measurements at each temperature point are shown in Fig 2. Increases in absorbance correlate to increasing opacity, resulting from the sol-gel transition process for thermoresponsive polymers. The LCST of poly(NIPAAm-co-DBA-coHPMA) was determined to be ~ 44 °C, thus validating a phase transition and LCST of poly(NIPAAm-co-DBA-co-HPMA) just above that of physiological conditions.

3.0

Absorbance (AU)

was utilized to initiate the polymerization, which proceeded for 12 h at 4 °C. The resulting polymer was precipitated in nanopure H2O at 50 °C, flashfrozen in liquid N2, and lyophilized for 2 d. The gel was rehydrated to 10% (w/v) using nanopure H2O.

2.5 2.0 1.5 1.0 0.5 0.0 36

38

40

42

44

46

Temperature (oC)

48

50

Figure 2. LCST measurement of poly(NIPAAm-co-DBA-coHPMA)

Further characterization and future studies include cytotoxicity tests, a viral vector release study, and total degradation time. Cytotoxicity test will help to determine the viability of the incorporation of this gel into medical procedures, while the release and degradation study will help to further characterize the gel’s biomechanical properties over time.

Incorporation of AA and a decrease in ratio of HPMA/DBA will also be studied in an effort to lower the LCST of the copolymer below that of physiological temperatures.

REFERENCES 1. Klouda L, et al. Eur J Pharm Biopharm 68(1):34-45, 2008.

2. Vernon BL, et al. Biomacromolecules 8(4):1280, 2007.

3. Vernon BL, et al. Macromolecules 40:3840, 2007.

4. Vernon BL, et al. Macromol Biosci 54:418, 2005.

5. Vernon BL, et al. Biomacromolecules 8:1280, 2007.

6. Sheardown H, et al. Acta Biomater, 8(7): 2517, 2012.

ACKNOWLEDGEMENTS Partial funding was provided by PPG, CMI, and the Coulter Award. Additional thanks to Dr. Michael Washington and the Fedorchak lab team.

COLLAGEN FIBER ORIENTATION MAPPING WITH FOURIER PTYCHOGRAPHY POLARIZED LIGHT MICROSCOPY Eric Zhang, Bin Yang, Ian A. Sigal Laboratory of Ocular Biomechanics, Departments of Ophthalmology and Bioengineering University of Pittsburgh, PA, USA Email: erz12@pitt.edu, Web: OcularBiomechanics.com state, raw images were acquired under sequential INTRODUCTION Detailed and accurate collagen fiber microstructure illumination from a 3x3 LED array. The same information is critical for understanding eye section was also imaged with standard PLM, as per biomechanics, physiology, and pathology. Rich the protocols described in [1]. structural information of the optic nerve head (ONH), in the back of the eye, can be obtained DATA PROCESSING FP processing was implemented in MATLAB using polarized light microscopy (PLM) [1]. following the algorithm of Zheng et. al [3]. Briefly, However, PLM, like other conventional microscopy techniques, suffers from the tradeoffs between field it utilizes phase retrieval and aperture synthesis techniques to achieve high synthetic NA. It of view (FOV) and resolution. Typically, the iteratively stitches Fourier spectra of the images solution is to stitch multiple high resolution images under different directional illuminations to generate into one with large FOV. However, this renders a synthetic Fourier spectrum containing high spatial image acquisition and post-processing time frequency contents which are typically not imaged consuming and prone to artifacts. Recently, Fourier with conventional imaging systems. ptychographic (FP) imaging was developed to Experimentally, this is accomplished via sample bypass tradeoffs by utilizing phase retrieval and illumination from singular LEDs at various angles aperture synthesis techniques [2]. With FP, high resolution and large FOV may be achieved without from the sample, which correspond to proportional mosaicking. We prototyped an FP-PLM imaging Fourxier spectrum shifts in the Fourier space [3]. system and used it to obtain simultaneous high We reconstructed a high resolution image of the resolution and large FOV images of ONH collagen fiber orientation.

ONH at each of the four polarization states [3].

High resolution FP-reconstructed images were later used to generate FP-PLM collagen fiber orientation METHODS maps using the methods described by Jan et. al [1]. i. Sample Preparation For comparison, the collagen fiber orientation map A pig eye (<2 years old) was obtained from a local slaughterhouse and fixed overnight in formalin of the same section was also generated using (10%) within 24 hours of death. Following fixation, standard PLM at 6.4x magnification. With both FPPLM and PLM based fiber orientation maps, we the eye was cryosectioned coronally into 20µm conducted quantitative analysis to assess the thick sections. ii. Imaging system development and imaging accuracy of collagen fiber orientation mapping accuracy using two techniques.

We developed a custom FP-PLM imaging system based on an upright dissecting scope (Olympus, SZX16). A programmable 32x32 RGB LED panel RESULTS Directional illumination of the sample was achieved was used for directional illumination. Polarization with a 32x32 RGB LED panel and controlled using filters were inserted to illumination and imaging Python scripts and a Raspberry PI 3. Automated paths. Images were acquired with a CMOS camera image acquisition was simultaneously achieved (ORCA Flash 4.0 LT) with a 3.2x/0.12 numeric with PI-controlled external voltage triggers to the aperture (NA) objective. Custom control software CMOS camera and image processing with custom was developed in both LabVIEW and Python to LabVIEW code. Thus total acquisition time has automate illumination and image acquisition. We been minimized to the product of exposure time and imaged a section of the ONH under four array size. This resulted in 2-3 fold decrease in polarization states (0°, 45°, 90°, 135°). For each po

acquisition time compared with traditional imaging systems under manual operation.

With FP, we obtained high resolution images with a 4x improvement in resolution when compared with conventional counterparts. These FP images were used to generate a fiber orientation map (FP-PLM) which, when compared with standard PLM, allowed more detailed and precise visualization and measurement of collagen orientation, including crimp patterns, in both the sclera and lamina cribrosa shown in Fig. 1. FP Images with large FOV of the ONH were obtained more slowly than when acquiring standard mosaics, due to burden of increased file size and hardware processing limits, however stitching artifacts were eliminated.

Wide Field

FP-PLM

Close Up

90° 0°

180°

b)

PLM

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d)

90°

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180°

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Figure 1. Fiber orientation maps of a pig ONH section with FPPLM (a and b) or regular PLM (c and d). Color indicate local pixel-scale fiber orientation, whereas white lines are added to indicate the mean orientation of a local region. Closeups of a small region of interest show further details (b and d).

Individual fiber bundles are better observed in the FP-PLM DISCUSSION images.

Collagen fiber orientation was effectively visualized with enhanced rendering of individual fiber paths and fiber bundle definition (Fig. 1). Increased resolution using FP-PLM allowed for more precise orientation marking as indicated by the white lines.

However, there is still room for improvement, and further advances in image quality may lead to superior fiber orientation mapping.

Although Zheng et. al has previously shown resolution improvements at illumination arrays of up to 19x19 with standard FP [2], the intensity reducing effects of light polarization severely constrain sample illumination beyond the 3x3 array used in this study. Since current exposures are already long and susceptible to motion-induced artifacts, higher LED intensity is needed to adjust the system and improve imaging speed.

We have demonstrated that FP-PLM can significantly improve resolution of PLM for ONH tissues, while avoiding stitching artifacts. FP-PLM is a promising technique for imaging collagen fiber architecture of the eye, and perhaps of other soft tissues. Nevertheless, improvements in acquisition and reconstruction are necessary for FP-PLM to reach the full potential of FP and PLM. REFERENCES [1] Jan, Ning-Jiun, et al. "Polarization microscopy for characterizing fiber orientation of ocular tissues." Biomedical optics express 6.12 (2015): 4705-4718.

[2] Zheng, Guoan, Roarke Horstmeyer, and Changhuei Yang. "Wide-field, high-resolution Fourier ptychographic microscopy." Nature photonics 7.9 (2013): 739-745.

[3] Zheng Guoan, 2016, Fourier Ptychographic Imaging A MATLAB Tutorial, Morgan & Claypool Publishers, San Rafael, CA, 95 p.

ACKNOWLEDGEMENTS This project was co-supported by the laboratory of Ocular Biomechanics (NIH R01 EY023966 and the Swanson School of Engineering at the University of Pittsburgh.

THE EFFECTS OF AN OSTEOARTHRITIS UNLOADER BRACE ON KNEE JOINT SPACE DURING GAIT Shumeng Yang, Kanto Nagai, MD PhD, William Anderst, PhD Biodynamics Lab, Department of Orthopaedic Surgery, Department of Bioengineering University of Pittsburgh, PA, USA Email: shy41@pitt.edu, Web: http://bdl.pitt.edu/ INTRODUCTION Osteoarthritis (OA) is one of the most common chronic joint conditions, affecting an estimated 27 million Americans [1]. The knee is the most commonly affected joint, with approximately 6% of US adults 30 and older living with symptomatic OA in the knee, and the medial compartment is more commonly affected than the lateral compartment during normal gait [2,3]. OA unloader braces are a noninvasive treatment believed to reduce pain, improve function, and possibly slow OA progression by unloading the medial compartment of the knee.

Previous studies have determined the effect of OA unloader braces using techniques including force sensors, torque analysis, and two-dimensional fluoroscopy [3,4]. These results are limited by a lack of in vivo quantitative data for joint space and a failure to quantify the external load applied during gait. The purpose of this research was to quantitatively evaluate the effects of a DonJoy OA unloader brace on dynamic joint space during level walking.

It was hypothesized that medial compartment joint space would increase and ground reaction force (GRF) would decrease when wearing the OA unloader brace.

METHODS 10 patients (Age: 52±8years; 8 male, 2 female; BMI: 27±4) with symptomatic OA primarily in one knee were tested after using the brace (Defiance, DonJoy Inc.) at least 2 hours daily for at least 2 weeks. Testing consisted of walking on an instrumented treadmill (Bertec Corp, Columbus, OH) at 1.0 m/s within a biplane radiography system.

Three trials were collected for each condition, braced and unbraced walking, in a randomized order. Patient-specific high resolution CT scans of the knee (0.4 x 0.4 x 1.25 mm) were segmented and reconstructed into three-dimensional bone models (Mimics, Marterialise, Inc. Leuven, Belgium)

Synchronized biplane radiographs were acquired at 100Hz using a Dynamic Stereo X-ray system, positioned to obtain anterior-superior and anteriorinferior views of the knee during gait while eliminating occlusion of bony details by the brace.

Model-based tracking was used to measure bone motion (Figure 1). This method has been validated for tracking the femur and tibia and has a reported accuracy of 0.9° or better in rotation and 0.7 mm or better in translation [6]. The ground reaction force, normalized to each subject’s body weight, was measured at 1000 Hz using the instrumented treadmill.

Figure 1: The model-based tracking technique using femur. This method optimizes the correlation between radiographs taken by the biplane X-ray system with the model obtained from the CT images, which determines exact pose at each frame.

the the 3D the

The medial tibial plateau was divided into 9 regions (Figure 2), and the average minimum joint space in the region with smallest space was selected for statistical analysis. Joint space was calculated by measuring the minimum distance from each point on the subchondral bone surface of the tibia to nearest point on the subchondral bone surface of the femur. Average joint space for each of the 9 regions and ground reaction forces were measured over 10% intervals for the first 40% of the gait cycle starting at heelstrike. The time of heelstrike and gait cycle lengths were determined using GRF data from

the treadmill. The difference in joint space and ground reaction force between the braced and unbraced conditions during level walking, was evaluated using two-way repeated-measures ANOVA.

showing that the increase in medial compartment joint space was the result of bracing, and not decreased loading. This suggests the use of an OA unloader brace could reduce cartilage loading in OA-damaged areas of the tibiofemoral joint.

There is conflicting evidence on whether OA braces significantly affect tibiofemoral medial compartment joint space. These findings agree with several previous studies [4, 5], however Haladik et al. found no significant difference in medial joint space with brace use [7]. These discrepancies could be due to several factors including testing procedures, measurement methods, and patient populations.

RESULTS Medial compartment joint space increased when using the OA unloader brace by an average of 0.27  0.15 mm (range: -0.04 to 0.92 mm, with negative values indicating a decrease in joint space after bracing) (ANOVA: p=0.004) (Figure 3A). The greatest average difference in joint space was 0.4 mm, observed during the first 10% of the gait cycle.

The smallest average difference in joint space was 0.2 mm, observed during the second 10% of the gait cycle. No differences in GRF were observed with and without brace use (mean 0.019 % body weight, ANOVA: p=0.15) (Figure 3B).

A

Average Joint Space (mm)

DISCUSSION The main finding of this study is that medial compartment dynamic joint space increased when wearing an OA unloader brace. This difference was present from heel strike through mid-stance phase.

There was no significant difference in GRF between braced and unbraced trials, 4 3.5

P=.007

P=.001

3

P=.028

P=.017

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Unbraced

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30-40%

This study includes several limitations, including a small sample size and lack of data for the push-off phase of the gait cycle. Future work may include examining the effect of bracing on lateral compartment joint space and joint stability.

REFERENCES 1. Jordan et al. Ann Intern Med, 133: 635-646, 2000 2. Ramsey et al. Sports Health, 1: 416-426, 2009 3. Pollo et al. Am J Sports Med. 30: 414-421, 2002 4. Komistek et al. J Arthroplasty, 14: 738-742, 1999 5. Dennis et al. J Arthroplasty, 21:2–8, 2006 6. Anderst et al. Med Eng Phys 31:10–16, 2009 7. Haladik et al. Knee Surg Sports Traumatol Arthrosc. 22:2715–2720, 2014 ACKNOWLEDGEMENTS This project was funded by DonJoy Orthopaedics, the Swanson School of Engineering, and the Biodynamics Lab. The Defiance braces were provided by DJO, Inc. B

Average GRF (% body weight)

Figure 2: The medial tibial plateau divided into 9 regions.

Region 5 was selected for 9 of the 10 subjects, and region 8 for 1 subject.

100 80 60 Braced

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20 0 0-10%

10-20% 20-30% 30-40% % Gait Cycle

Figure 3: Average medial compartment joint space (A) and average ground reaction force (B) over 10% intervals from heelstrike to terminal stance in braced and unbraced conditions. Data shown as mean  1 SE. (A) Medial compartment joint space was significantly greater with the brace. (B) No significant difference was observed in GRF.

MODULATING INFLAMMATION THROUGH CARTILAGE-DERIVED EXTRACELLULAR MATRIX FOR POTENTIAL TREATMENTS OF CARTILAGE DISEASE Madalyn R. Fritch, Drs. He Shen, Hang Lin, Rocky Tuan Center for Cellular & Molecular Engineering, Department of Orthopedic Surgery University of Pittsburgh, PA, USA Email: mrf50@pitt.edu, Web: http://ccme.pitt.edu/ INTRODUCTION Cartilage damaged by trauma, disease or aging demonstrates very limited capabilities for selfregeneration and ultimately results in osteoarthritis (OA), a degenerative joint disease with a high prevalence in the U.S. (27 million affected; 25% in >50 population) [1]. Moreover, initiation of OA often starts with pathologic activation of resident chondrocytes, followed by production of proinflammatory factors and other degradative enzymes [2]. Additionally, macrophages in arthritic joints are often activated from a nonpolarized, M0 state to a polarized, M1 state which produce more pro-inflammatory factors, thus furthering degeneration of cartilage [3].

This study investigated the therapeutic potential of articular cartilage extracellular matrix (cECM) on cartilage health and macrophage state, to lay the groundwork for future applications of cECM injection for the prevention or treatment of OA. Urea-extracted, soluble ECM from articular cartilage has been shown to independently upregulate early chondrogenesis of encapsulated human mesenchymal stem cells (hMSCs) and synergistically enhance chondrogenesis when exogenous TGF-β is added as a medium supplement [4]. Additionally, soluble ECM has been previously shown to induce M2 phenotype, while artificial biomaterials induced M1 [5]. Thus, this study hypothesized that cartilage-derived, urea extracted soluble ECM will inhibit inflammation by suppressing M1 pro-inflammatory secretion, thus rescuing inflammation-associated cartilage degeneration; if successful, this method will present a new, potential treatment for OA. METHODS Soluble ECM was extracted from bovine cartilage via urea according to our previous work (Rothrauf, et al. 2017). Macrophages (RAW264.7) were classically polarized to an M1 state using

interferon-γ (IFN- γ) and lipopolysaccharide (LPS) via previously established induction protocols [6].

Urea-extracted soluble cECM was added 24 hours later at 100 μg/ml to assess its effect on macrophage polarization. Bovine serum albumin (BSA) was similarly added at an equivalent cECM concentration as a protein control. In this study, we examined the treatment effect on cartilage constructs derived from primary human chondrocytes or MSCs, which were loaded 3D photocrosslinkable PDLLA-PEG scaffolds and subjected to chondrogenesis according to our previous work [7]. The cartilage scaffolds were cultured in pro-inflammatory cECM containing media conditioned by M1 or M0 macrophages to induce an OA-like environment or control medium, respectively. After 7 days incubation, the health of engineered cartilage was examined by real-time polymerase chain reaction (RT-PCR). Inflammatory markers such as pro-inflammatory cytokines (IL-6, IL-1β) and nitric oxide (NO) in the medium were also analyzed by enzyme-linked immunosorbent assay (ELISA) and Griess assay.

RESULTS M0 to M1 macrophage polarization, via IFN-γ and LPS treatment, significantly enhanced the production of NO, IL-1β, and IL-6 indicating successful establishment of pro-inflammatory M1 polarized macrophages. Following polarization, macrophages were treated with decellularized, ureaextracted soluble cartilage ECMs. The effect of cECM on macrophage state was analyzed by performing ELISA on macrophage conditioned media and observed to decrease IL-1β secretion significantly but not affect IL-6 secretion for both M0 and M1 macrophages.

The effect of M0 and M1 macrophage conditioned media, with or without ECM treatment, was evaluated on human cartilage-derived and hMSCderived chondrocytes in 3D cultures and quantified

via real time PCR (See Figure 1). Pro-inflammatory conditioned medium from M1 macrophages caused a significant decrease in gene expression of collagen type II (COL II) and increased expression of metallopeptidase 13 (MMP13), suggesting an early sign of degeneration. Comparatively, proinflammatory media treated with soluble cECM reduced gene expression of the inflammatory marker IL-1β and MMP13 in hMSCs cultured in M1 pro-inflammatory media. Soluble cECM seemed not able to rescue the phenotype loss in cells treated with M1 pro-inflammatory media, based on decreased chondrogenic markers, aggrecan (ACAN) and COL II expression. However, cECM did increase ACAN for both engineered cartilage types cultured in M0 conditioned media without inflammation.

Figure 1. Real time PCR relative gene expression analysis of chondrocyte and hMSC derived engineered cartilage in 3D scaffolds, showing the effects of a 7-day culture in M0 or M1 conditioned media with or without cECM treatment (n=2).

DISCUSSION Classical polarization via IFN-γ/LPS did induce M1-like macrophage state, which causes degeneration effect on articular chondrocytes and MSC-derived chondrocytes in 3D scaffold culture.

Urea-extracted, soluble cECM supplementation in M0 and M1 media did reduce NO secretion and

reduced M0 macrophage inflammatory cytokine secretion but not significantly for M1 macrophage.

Soluble cECM addition did improve some chondrogenic gene expression in M0 media treated engineered cartilage, but did not significantly rescue chondrogenic gene expression in M1 proinflammatory media treated engineered cartilage.

Therefore, cECM may be a promising preventative treatment in addition to current methods to maintain healthy cartilage phenotype in an already noninflammatory state. Additionally, cECM presents a potential benefit in reducing inflammation in hMSCs-derived cartilage that can be applied to current OA treatments.

REFERENCES 1. Zhang Y, et al.

Epidemiology of osteoarthritis. Clinics in Geriatric Medicine.

2010;26(3):355-369.

2. Sokolove J, et al. Role of inflammation in the pathogenesis of osteoarthritis: latest findings and interpretations. Therapeutic Advances in Musculoskeletal Disease. 2013;5(2):77-94.

3. Laria A, et al. The macrophages in rheumatic diseases. Journal of Inflammation Research.

2016;9:1-11.

4. Rothrauff BB, et al. Tissue-specific bioactivity of soluble tendon-derived and cartilage-derived extracellular matrices on adult mesenchymal stem cells. Stem Cell Research & Therapy. 2017;8:133.

5.Petrosyan, et al. A step towards clinical application of acellular matrix: A clue from macrophage polarization. Matrix Biology.

2017;57:334-346.

6.Liu, Chao-Ying et al. M2-polarized tumorassociated macrophages promoted epithelialmesenchymal transition in pancreatic cancer cells, partially through TLR4/IL-10 signaling pathway.

Laboratory Investigation. 2013;93:844–854.

7. Sun, A et al. Chondrogenesis of human bone marrow mesenchymal stem cells in 3dimensional, photocrosslinked hydrogel constructs: Effect of cell seeding density and material stiffness.

Acta Biomateriala.

2017;58:302-311.

ACKNOWLEDGEMENTS The authors would like to thank Dr. Jian Tan for MSC isolation and characterization, and Dr. Benjamin B Rothrauff for providing cartilage powder. Partial funding provided by the Swanson School of Engineering Summer Internship Program.

EXAMINATION OF TISSUE VIABILITY AND HOMEOSTASIS IN AN OSTEOCHONDRAL BIOREACTOR Kalon J. Overholt, Rocky S. Tuan, and Riccardo Gottardi Center for Cellular and Molecular Engineering, Department of Orthopaedic Surgery University of Pittsburgh, PA, USA Email: kjo34@pitt.edu, Web: http://ccme.pitt.edu/ INTRODUCTION Osteoarthritis (OA) is a debilitating joint disease characterized by the degradation of articular cartilage and subchondral bone [1]. While palliative treatments can relive the symptoms of OA, no current treatments can halt or reverse the damage of OA. A better definition of the mechanism of OA pathogenesis is essential for the identification of therapeutic targets and the subsequent screening of disease-modifying drugs. A locus of the disease has been identified at the osteochondral (OC) junction, indicating that biochemical communication between bone and cartilage tissues may play a crucial role in the overall mechanism of OA [1]. A sufficient understanding of the interactions between these tissues requires that they be studied as a single unit, introducing the need for an in vitro osteochondral model.

Despite their proximity, bone and cartilage occupy extremely different environments in vivo.

Cartilage is avascular, hence, chondrocytes (cartilage cells) thrive in a hypoxic environment low in glucose. Osteoblasts (bone cells) require a vascular network to supply a normoxic, glucose-rich medium [2]. The ideal conditions for bone are undesirable and potentially toxic for cartilage, and vice-versa.

Therefore, in vitro models have primarily focused on studying either bone or cartilage in isolation. The present study used a previously designed bioreactor which creates two adjacent microenvironments, allowing the culture of bone and cartilage together as an OC complex [3,4,5,6]. The bioreactor design consists of a row of wells, each with input and output channels and a central insert containing a tissue sample. The primary objective was to validate this system for drug screening and modeling of the OA disease process. We investigated the suitability of the system for maintaining homeostasis during longterm culture of native tissue. A viability period of 7 days was chosen as a success criterion, since experiments simulating OA inflammation can be completed within this time [6].

METHODS Native osteochondral tissue was obtained from juvenile farmed pig legs purchased at a local butcher shop. The knee joint capsule was dissected under sterile conditions. Osteochondral cores (n=28) were explanted from the distal femoral end using a 4 mm trephine (Salvin) on an automatic drill under continuous saline irrigation. The cores were then transferred to cell culture media.

Dual-chambered bioreactors (n=4) were 3Dprinted using a biocompatible stereolithography (SLA) resin as described in Lozito et al. [6]. In aseptic conditions, OC explants were loaded into the bioreactors. Tissue cores in bioreactors (n=8) were supplied with chondrogenic medium (CM) targeted at the cartilage component and osteogenic medium (OM) targeted at bone. Another group of cores in bioreactors (n=8) were supplied with a mix of 50% CM and 50% OM as a negative control. Media was stored in 20 mL syringes and perfused through this tissue at a flow rate of 5.52 mL/day. To compare culture conditions in the bioreactor to standard tissue culture, a positive control group of cores (n=12) were cultured in tissue culture plastic (TCP) wells in a 50/50 mix of media. The effluent media from bioreactors and supernatant from TCP wells was collected in glass vials and frozen at 2, 4, 6, and 7 days for storage. Supernatant from TCP wells was collected and frozen at the same timepoints. The entire bioreactor apparatus was stored in a tissue culture incubator at 37° C and 5% CO 2 . After 7 days, the tissue cores were collected for further analysis.

DATA PROCESSING Viability of tissues was evaluated using a Live/Dead Cell Viability Assay (Thermo Fisher). On day 0 and day 7, cores were bisected axially and incubated in Live/Dead solution (phosphate-buffered saline (PBS), calcein-AM, ethidium homodimer-1) for 20 minutes. Samples were then rinsed in PBS and imaged under a fluorescent microscope. The images were analyzed for qualitative signs of cell death.

RESULTS Through live/dead staining we determined that substantial bone and cartilage cell death occurred in both bioreactors supplied with a 50/50 mix of media.

In both bioreactors supplied with separate media streams, we observed viability in cartilage and substantial cell death in bone. Osteochondral cores cultured in TCP wells maintained cell viability in both cartilage and bone. The experiment was repeated with new tissue. In the repeated experiment (Figure 1) there was no substantial death in the bioreactors supplied with a 50/50 media mix or in those supplied with separate media.

A

C

B

D

Figure 1. Results of live/dead viability staining in a repeated experiment. (A) and (B) shows viability in a representative sample with 50/50 media mix. (C) and (D) show a sample from bioreactors with separate osteo/chondro media.

The quantitative GAG assay of effluent media also showed that GAG mass loss paralled levels of cell death (Figure 4). Mass loss in bioreactors with separate O/C media streams was not statistically different from loss in plated culture. Tissues cultured in 50/50 media bioreactors showed the greatest GAG loss. This difference has not yet been statistically analyzed. Additionally, the loss of GAGs showed a decreasing trend throughout the duration of the experiment.

Mass Loss (μg)

Loss of sulfated glycosaminoglycans from cartilage was determined through a colorimetric assay of the effluent media with 1,9-dimethylmethylene blue (Biocolor). A standard curve was prepared using dilutions of chondroitin 4-sulfate as the reference standard. Samples of media from TCP wells and combined top and bottom bioreactor streams were assayed after 2, 4, 6, and 7 days.

Absorbance was recorded using a microplate reader.

Measured GAG concentrations were converted to total mass lost and divided by the number of tissue cores to produce mass lost per tissue sample.

350 300 250 200 150 100 50 0

OC Bioreactor 50/50 Bioreactor 50/50 Plate

2

4

6

7

Days Figure 4. Results of the colorimetric glycosaminoglycan (GAG) assay.

DISCUSSION Our results indicate that it is possible to preserve cartilage viability inside of our bioreactor. In the first experiment, substantial cell death occurred in cartilage in 2 of 4 bioreactors. By repeating the experiment, we showed that cartilage can remain viable in all bioreactors tested. The cause of the original cartilage dieback has not yet been identified.

We hypothesize that unfavorable conditions such as contamination and insufficient perfusion may have contributed. To increase bone health in the bioreactor, we plan to increase perfusion through bone and increase dissolved oxygen tension.

Our analysis of GAG loss showed that tissues in TCP and in bioreactors with separate media lost comparable amounts of GAGs (Figure 4). We interpret this result to mean that the microenvironments in our bioreactors and in TCP wells are biochemically similar. GAGs are most quickly lost from dead cartilage. In samples where cartilage health was maintained, GAG loss was noticeably lower. For this reason, we predict that GAG levels in effluent media can serve as a marker of cartilage homeostasis and viability during longterm culture.

REFERENCES 1. Goldring et al. Nature Rev Rheumat, 12(11), 632–644.

2. Honner, et al. J Bone & Joint Surj, 53(4), 742–8.

3. Lin et al. J Molecular Pharmaceutics 2203-2212.

4. Gottardi et al. Orthopaedic Res Society, 5.

5. Alexander et al. Exp Biol & Med, 1080–1095.

6. Lozito et al. Stem Cell Res & Therapy, 4(Suppl 1), S6.

ACKNOWLEDGEMENTS This work was generously supported by the University Honors College Health Sciences Fellowship at the University of Pittsburgh, the Ri.MED Foundation, and CASIS GA-2016-236.

FOUR-POINT FORTUNE-TELLER-INSPIRED ORIGAMI GRASPER FOR INCREASED DEXTERITY AND LESS TISSUE DAMAGE IN MINIMALLY INVASIVE SURGERY (MIS) 1 Hannah Liu , BokSeng Yeow2 and Hongliang Ren.2ǂ 2

1 Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA 15260, USA Department of Biomedical Engineering, National University of Singapore, 117575 Singapore ǂ Corresponding author: ren@nus.edu.sg.

Email: hkl11@pitt.edu, Web: http://bioeng.nus.edu.sg/mm/ DESIGN CONCEPTUALIZATION/METHODS INTRODUCTION To rectify the problem of tissue injury we created a MIS has become an increasingly viable alternative to device with a larger surface area—if the same load, open surgery as its health benefits have been coupled weight of the tissue, is applied to an instrument with with novel technologies that seek to provide high a larger surface area, there will be less overall dexterity and maximal grip while passing through induced stress as per the compressive stress equation. millimeter incisions/orifices. MIS reduces risk of The common origami fold called the “fortune teller” infection, duration of surgery and recovery time, and fulfils this requirement, as it can grab a tissue at four induces less trauma through the use of tethered tools points as opposed to just two. This implies for an externally controlled operation [1]. Traditional possibility for greater force control and distribution. two-point graspers are used to physically manipulate tissue and these devices must fulfil two aspects: 1) Our fortune-teller inspired design is slightly different high dexterity, and 2) high power-to-weight ratio that to the traditional fold as there is a 1.4 cm x 1.4 cm incurs as little tissue trauma as possible [2]. area of free space between the four quadrants, as seen in Figure 1. This feature attempts to appeal to Origami applications to MIS are appealing as the increased dexterity/force control as it raises the instrument can be shrunken down for insertion number of spherical mechanisms from one to four, during keyhole surgeries—known as flat where spherical mechanisms are the “source of foldability—but can subsequently deploy inside the motion in the kinematic origami models” [3]. The 3D body to provide a high number of degrees of freedom printed models were designed using Solidworks (dof) under loading conditions—known as action 2016 and printed in Tango Black FLX9070, a origami [3]. Advances in device dexterity can be flexible material, in an Object260 Connex3 printer. attributed to the inspiration of origami-graspers, compliant mechanisms that move through Fig. 1 (a) Opening actuation of the smaller inverted fortune teller within twisting/bending, allowing for new actuation the larger paper model with an upward a) methods. However, errors resulting in tissue injury Grasper motion of a rod. (b) One string is threaded through two corner folds at can be attributed to traditional graspers in 66% of two anchorage points and pulled cases, “with 13% of these due to excessive force” [4]. downward to actively close the Base b) origami, shown in paper and 3D Therefore, this paper will focus on the structure, Tendon printed with width of 47.5 mm. (c) dexterity, and opening/closing ability of an Twisting method of actuation where four tendons converge in the center of alternative four-point fortune-teller design which the origami and the twisting actuator primarily works towards rectifying the issue of creates force output and torque to c) Rod close the device mechanically induced tissue injury while still Additionally, three actuation methods were providing maximal dexterity. Origami folding compared for this device. To open the origami, we principles were consulted for conceptualization, tethered a smaller, inverted fortune teller with plastic while paper and 3D models were fabricated to carry tendons within the larger fortune teller design. A rod out a comparative study of actuation methods passes through the center of both origamis and through quantitative measures. presses up against the center of the inverted design, as in Figure 1. As the inner origami expands, so does

the outer design. To close the origami, we tested a tendon driven one, where a single plastic tendon is threaded between two corner folds, about two-thirds up the crease. This method takes advantage of the relationship between the folds at the center of the origami—as one pulls the tendons in a downward motion, two corners are directly actuated inward, while the other two corners will similarly move in that direction. Another closing method takes advantage of the flat edges of the origami design rather than the four corners. A tendon is knotted through each opposing flat edge and these two tendons converge at the center of the device on a rod.

When this rod is twisted in either direction, the four corners clamp together in an inward/rotating motion.

After twisting the rod 90° clockwise (CW), two sides fully close, while twisting the rod 90° counter clockwise (CCW) brings the other opposing sides together, as seen in Figure 1. Rotating the rod 360° CCW/CW brings all four corners to the center. We gathered quantitative data regarding force output/torque for paper models (using a 6 dof ATI sensor), range of motion/coverage, as well as grasping capability using 3D models.

this value for the entire length of application. Also its greater fluctuation in “z” torque may prove to be useful for manipulation purposes. The twisting method is able to grab relatively heavy objects with all four corners, while the tendon method cannot, and thus can provide surgeons with more dexterity and control when performing surgery; changing the number of degrees in which the rod is rotated as well as the direction (CW/CCW) consequently changes the sides of the origami that are brought together, allowing for pair-pair fold control. Further studies should include designing an attachment to the ATI force sensor in order to grab it in a way that would confer more accurate sensor readings. Force output needs to be maximized as well—5-7 N is usually acceptable within the body. Also, a force input sensor can be applied in future experiments in order to have a consistent pulling or twisting force applied during each actuation method—this way comparisons between each method can be validated.

With our current design, compressibility is a large aspect that needs to be further explored, but we were able to create a 40% scaled-down version of our larger model, indicating scalability of the design.

RESULTS All results are summarized in Table 1.

REFERENCES 1.Fernandes et al. Materials Today 12.10, 14-20, 2009 2.Salerno et al. 2014 IEEE International Conference on Robotics and Automation 2014.

3.Bowen. All Theses and Dissertations, Paper 3685, 2013 4.Chandler et al. IEEE Trans Biomed Eng 2017 ACKNOWLEDGEMENTS Dr. Eric Lagasse, University of Pittsburgh Swanson School of Engineering, Office of the Provost, Study Abroad Office and Singapore Academic Research Fund under Grant R-397-000-227-112, NUSRI China Jiangsu Provincial Grant BK20150386 & BE2016077 awarded to Dr. Hongliang Ren.

DISCUSSION Concerning the smaller inverted fortune teller within the larger design, this method is efficient in equally distributing the force of a single transverse movement. Surgeons can also be informed to modulate the amount of upward movement to incur a different amount of expansion. Out of the two closing methods—tendon and twisting actuation— we believe the twisting method to be a stronger candidate for future studies. While the tendon method reached a higher force output, the twisting method approaches 1 N almost instantly and stays at Table 1 OPENING Smaller Inverted Fortune Teller CLOSING Tendon Driven (higher actuation point) Twisting

Force Input/ Output

Range of Motion/Coverage

DOF

Force input is equally spread and can 100% open the device

Area coverage increases from 2.25 cm2 to 10.56 cm2 upon actuation

2

N/A

Maximum force vector magnitude=1.1 N large torque in “x” and “y” Maximum force vector magnitude= 0.83 N; steadier force vector magnitude over time; more fluctuation in “z” torque

Only two corners fully close, while the others move around 4 mm closer Modulating amounts of closure by twisting clockwise/counterclockwise 90°, or fully close by twisting 360°

2

Unable to grasp fully (only 2 corners are successfully actuated, so objects fall out of grip) Grasps grape-like object made of silicone (1-gram, 15 mm radius) and miscellaneous object (28-gram, 8 mm radius)

3

Grasping Ability

REACTION TIMES TO INTRACORTICAL MICROSTIMULATION IN A PERSON WITH TETRAPLEGIA ARE SIMILAR TO THOSE OF PERIPHERAL TACTILE AND VISUAL STIMULI IN ABLE-BODIED SUBJECTS Grace A. Brueggman1, Jeffrey M. Weiss1,2, Robert A. Gaunt, PhD.1,2,3, Jennifer L. Collinger, PhD.1,2,3,4 1

Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, USA., 2Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA 15213, USA., 3Center for the Neural Basis of Cognition, Pittsburgh, PA 15213, USA., 4Department of Veterans Affairs Medical Center, Pittsburgh, PA 15206, USA. Email: gbrueggman@pitt.edu Web: http://www.rnel.pitt.edu/ INTRODUCTION Brain-computer interfaces (BCI) can decode neural activity recorded from microelectrodes and enable people with paralysis to control a multiple degreeof-freedom robotic limb [1]. However, this technology relies heavily on visual feedback and provides the user with little information about object contact or grip force. Including somatosensory feedback in BCI systems may improve limb dexterity and performance.

testing amplitudes for each subject are reported in Table 1.

Intracortical microstimulation (ICMS) can elicit tactile percepts [2], but it is unknown how quickly a person can perceive and react to ICMS feedback and how these reaction times compare to natural somatosensory feedback. We expect that ICMSbased feedback will be most useful if reaction times are comparable to those of natural tactile stimuli.

Table 1: All Subjects’ Mean Electrical Stimulation Threshold and Testing Amplitude

METHODS A 30-year old male subject with a C5/C6 spinal cord injury (SCI) was implanted with four Utah microelectrode arrays, including two arrays in primary somatosensory cortex. We tested reaction times to single-electrode ICMS at 100 µA using 500 ms, 100 Hz pulse trains. Responses were collected using a bite switch. We compared ICMS reaction times to 500 ms duration LED pulses and surface electrical stimulation of the index finger (500 ms, 100 Hz pulse trains) using an amplitude with a similar reported intensity to the ICMS stimulation.

The visual and electrical stimulation conditions were repeated in 3 able-bodied, right-hand dominant subjects. Electrical stimulation was tested at 1.3-1.75x of threshold, which is similar to the intensity tested with the SCI subject. Threshold and

Electrical Stimulation Amplitude (mA)

Subject Condition (mA)

SCI

ABC01

ABC02

ABC03

Threshold

2.19

1.50

0.770

1.66

Testing

3.20

1.95

1.40

2.91

60 trials were performed for each stimulus condition. Stimuli were delivered after a random delay during a 4 second period. Catch trials without any stimulus occurred 5% of the time. After a set of 20 trials, the subjects reported the intensity of the stimulus on a visual-analog scale (VAS). This value was used to monitor any unintentional changes in stimulus intensity throughout the experiment. If significant changes in stimulus intensity were observed during tactile stimulation, a new electrode was applied, and the subject’s threshold was revaluated.

RESULTS The subject with SCI had median reaction times to electrical, visual, and ICMS stimuli of 299.4 ms, 329.5 ms, and 305.3 ms respectively.

A 1-Way Kruskal-Wallis test revealed a significant difference in reaction time between modalities (p < 0.05) for the subject with SCI. Post-hoc pairwise comparisons showed that reaction times were significantly faster to ICMS than electrical

stimulation (p < 0.001, Wilcoxon Rank-Sum), but no other significant differences were noted.

Figure 1: Distribution of reaction times to electrical, visual, and ICMS stimuli modalities measured in a person with SCI.

The median reaction time of all able-bodied subjects to electrical and visual stimulation respectively were 350.5 ms and 289.2 ms.

DISCUSSION Overall, the subject with SCI had a comparable reaction time to visual stimuli as the able-bodied subjects, which is to be expected since the injury should not have impacted his vision or ability to respond with a bite switch. Additionally, his reaction time to peripheral electrical stimulation was similar to that of the able-bodied subjects, and actually faster by approximately 20 ms, indicating that his peripheral reaction times were also in a normal range. Therefore, this suggests that his faster reaction time to ICMS over electrical stimulation reflects a true difference in his ability to perceive the stimuli and is not due to a slowed peripheral reaction time as a result from his injury.

Further testing in able-bodied subjects is needed to establish more definitive normative values as we observed variability across subjects. Compared to the able-bodied subjects, the subject with SCI had a higher threshold to electrical stimulation (due to residual peripheral tactile deficits) requiring a higher absolute value of delivered current, which may have impacted his results as reaction time is known to depend on stimulus intensity. Further testing is necessary to liken the perceived intensity of the electrical stimulation delivered during testing since there was a wide range of thresholds between subjects.

REFERENCES [1] Collinger et al. The Lancet. 381, 557-564, 2013.

[2] Flesher et al. Sci. Transl. Med. 8, 361, 2016.

[3] Barnett-Cowan et al. Exp Brain Res. 198, 221â&#x20AC;&#x201C; 231, 2009.

Figure 2: Distribution of reaction times to electrical and visual stimuli modalities in 3 able-bodied subjects.

Each subject had a significantly faster reaction time to visual stimuli when compared to electrical stimulation (all p < 0.01, Wilcoxon Rank-Sum test) which is consistent with previous work [3].

ACKNOWLEDGEMENTS Partial funding was provided by the Swanson School of Engineering and Office of the Provost.

This Fellowship occurred at the Rehabilitation Neural Engineering Laboratories at the University of Pittsburgh. This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) and Space and Naval Warfare Systems Center Pacific (SSC Pacific) under Contract No. N66001-16-C-4051 and the Revolutionizing Prosthetics program (contract number N66001-10-C-4056). Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DARPA or SSC Pacific.

TRIGGER RATE MONITORING FOR THE ATLAS EXPERIMENT AT CERN Daniel Zheng, Professor Tae Min Hong Department of Physics and Astronomy University of Pittsburgh, PA, USA Email: daniel.zheng@pitt.edu INTRODUCTION ATLAS is one of two general-purpose detectors at the Large Hadron Collider (LHC). It investigates a wide range of physics processes, probing previously unreachable phenomena such as the Higgs boson, the heavy strong sector, and possible new physics such as supersymmetry. Beams of protons are accelerated up to a center of mass energy of 13 TeV by the LHC. These beams cross and collide at the center of the ATLAS detector. Most of these collisions are uninteresting; the protons simply bounce off of each other. However, sometimes two protons undergo â&#x20AC;&#x2DC;hardâ&#x20AC;&#x2122; scattering, releasing the full 13 TeV of energy to produce new particles which interact and scatter out from the collision point into the detector.

Six different detecting subsystems arranged in layers around the collision point record the paths, momentum, and energy of the particles, allowing them to be individually identified. A large magnet system bends the paths of charged particles so that their momenta can be measured.

The readout from ATLAS detectors create an enormous flow of data. To digest the data, ATLAS uses an advanced â&#x20AC;&#x153;triggerâ&#x20AC;? system to tell the detector which events to record and which to ignore. Complex data-acquisition and computing systems are then used to analyze the collision events recorded. These data are then utilized by physicists all over the world to search for new phenomena. [1] METHODS Motivation. Over the summer, I worked on a multitude of software projects for ATLAS. This report will describe my work on Xmon, a trigger rate monitoring tool for the ATLAS trigger system.

The proton bunches cross at a rate of 40MHz and each of these bunch crossings create about one megabyte of data, and thus this is an enormous rate of data production of several terabytes per second.

ATLAS relies on the trigger system â&#x20AC;&#x201C; a series of hardware and software â&#x20AC;&#x153;triggersâ&#x20AC;? that select events to save [1].These triggers impose kinematic requirements on a variety of physics signatures which indicate interesting events, of which some such examples are electrons, energetic jets of particles, and missing transverse momentum. Each of these triggers

has a specific rate, and together form a menu which defines the composition of events which are saved.

This system reduces the bunch crossing rate of 40 MHz to 1 kHz.

Figure 1. June 2017 physics trigger rates as a function of time. Note the signatures (e.g. Electrons) each have a specific rate. [2]

These rates are of great importance to the collaboration, and ensuring the nominal operation of the detector and trigger system is a priority. In particle physics research massive amounts of data is required to make meaningful discoveries, and flaws in the TDAQ system can cause massive losses of data.

Making Predictions. The trigger rate falls with time due to the dropping in beam luminosity, because as the beams collide fewer protons make up eachy beam. However, these rates as a function of time are complex and arbitrary and follow no clear relation.

Cross-section is a type of probability expressed in units of area. The elastic scattering events have a 1 millibarn cross-section. One can imagine this as â&#x20AC;&#x153;how big the proton looks to another protonâ&#x20AC;?. The unintuitive extension of this is the cross-section for the previously mentioned physics signatures (e.g. electrons, jets), which also has an associated probability of occurring during a pp collision, or in other words, a cross-section.

This cross-section can be calculated analytically from only two free parameters, the trigger rate and the beam luminosity. Rate, R, has units of s-1 and the beam luminosity, đ??żđ??ż, has units of cm-2s-1. Thus one can derive cross-section for process â&#x20AC;&#x2DC;xâ&#x20AC;&#x2122; as:

đ?&#x153;&#x17D;đ?&#x153;&#x17D;đ?&#x2018;?đ?&#x2018;?đ?&#x2018;?đ?&#x2018;?â&#x2020;&#x2019;đ?&#x2018;Ľđ?&#x2018;Ľ =

đ?&#x2018;&#x2026;đ?&#x2018;&#x2026;đ?&#x2018;?đ?&#x2018;?đ?&#x2018;?đ?&#x2018;?â&#x2020;&#x2019;đ?&#x2018;Ľđ?&#x2018;Ľ(đ?&#x2018;Ąđ?&#x2018;Ą) đ??żđ??ż(đ?&#x2018;Ąđ?&#x2018;Ą)

This cross-section value is then plotted as a function of pile-up. Pile-up is a special kind of beam

parameter because it can impose â&#x20AC;&#x2DC;fakeâ&#x20AC;&#x2122; rate, which makes it appear that the trigger cross-section is changing. For certain triggers this relationship is flat with respect to pile-up, however for some which are sensitive to pile-up, this relationship is linear or exponential.

This cross-section relationship is then stored and placed in a configuration file which the online run control software can access. When a new data-taking run begins, Xmon is automatically launched and loads these relationships. The live luminosity and pile-up is queried about 3 times per second. From this information, the expected trigger rate can be calculated. This prediction is then compared against the live rates and plotted for 24/7 monitoring.

reworked, and a new C++ struct was added for the L1Topo ratio functionality. L1Topo is a new topological trigger processor that was added to the ATLAS trigger system this year, and applies kinematic and angular requirements to select more interesting physics events. Ensuring that the ratios of L1Topo triggers to similar L1 triggers is constant is an important way of verifying that the L1Topo trigger is functioning properly.

RESULTS Through an extensive commissioning process, the new Xmon adapter was tested and verified to be working. L1Topo ratio functionality was also tested and verified as shown in Figure 3.

Monitoring the Xmon predictions helps to identify malfunctions of the ATLAS detector, as shown in Figure 2.

Figure 3. A L1Topo muon trigger (red) and its associated predictions (green). (ATLAS Preliminary).

DISCUSSION

Figure 2. HLT tight electron at 26 GeV (HLT_e26_lhtight) rate was off from prediction due Transition Radiation Tracker (a detector subsystem) running at low voltage. The rate recovered after voltage issue addressed (2h).

DATA PROCESSING The current tool was separated into two different programs, one for the Level-1 (L1) and High-Level Trigger (HLT) system. I rebuilt the Xmon tool to merge L1 and HLT prediction adapters into a single adapter. I also added Level-1 Topological Trigger (L1Topo) ratio monitoring functionality, in order to help with the validation of this novel new system.

Live rate information is pulled from the ATLAS Information Service server. Using pile-up data, rate predictions are made for over 50 triggers and published to the Information Service server and then pulled and plotted by the TRP tool for display in the ATLAS Control Room.

Creation of the new adapter involved attaining an indepth understanding of the separate L1 and HLT code. Many C++ functions, and classes were

The rewritten Xmon adapter is now being used by ATLAS to monitor live trigger rates, and helps to ensure optimal functioning of the ATLAS detector.

Currently, Xmon can only perform a linear regression (first degree polynomial fit). While this works quite well for many ATLAS triggers, many triggers, like L1_XE60, are more complex and difficult to fit like this. Future work will involve adding higher-order polynomial fits to Xmon for complex triggers, as well as building a web interface to make the Xmon tool more accessible.

REFERENCES [1] ATLAS Collaboration. Performance of the ATLAS Trigger System in 2015. 2016. arXiv:1611.09661 [hep-ex] [2] ATLAS Collaboration. Trigger Operations Public Results.

ACKNOWLEDGEMENTS I'd like to thank my advisor, Dr. Tae Min Hong, as well as my mentor Andrew Aukerman for assisting me with this project.

Development of a 3D Printed, Low Cost Thumb Prosthetic Tyler J. Bray1, Skip Meetze2, Jon Schull, PhD.2, Alexander M. Spiess, MD3 1 University of Pittsburgh Department of Bioengineering, Pittsburgh, PA 2 Rochester e-NABLE Lab, Rochester, NY 3 University of Pittsburgh Medical Center Department of Plastic Surgery, Pittsburgh, PA Email: tjb100@pitt.edu INTRODUCTION There were 3341 traumatic thumb amputations between 2007 and 2010 in the United States alone.

Only 467 of those underwent a successful replantation of the severed thumb [1]. Although another reconstructive procedure, the toe-to-thumb transfer, is a popular and often successful procedure in the U.S., it is not necessarily as popular elsewhere. In more conservative cultures, such as some in Vietnam, amputees are less likely to elect for a transfer procedure because it includes disfiguring a second and currently healthy part of their body [2]. Prosthetic fingers are available in a range of appearances, functionalities and costs varying from hundreds of dollars to tens of thousands [3]. The advancements of 3D printing technologies in recent years has made it possible to introduce new, low-cost prosthetic options with customized size, functionality, and aesthetic design for those with upper-limb differences.

METHODS Our team developed a prosthetic thumb device that would allow the use of residual sensation in the palm by limiting the amount of plastic covering the hand. The distal end of the thumb is permanently flexed at 45 degrees to allow for easier opposition.

Prototypes have been developed with a compressible fingertip to help with gripping objects.

A series of prosthetic device prototypes has been developed using TPU 95A filament printed from an FDM 3D printer. This plastic is more elastic than the commonly used PLA and ABS plastics, thus allowing for greater flexibility and resilience as required by hand movement. The FDM printing technology has already been used to construct thousands of prosthetic devices like those of the eNABLE volunteer community. To efficiently produce a more accurate and comfortable device, our team has been able to use a digital scan of the amputeeâ&#x20AC;&#x2122;s hand, Autodesk Meshmixer and CAD programs.

DATA PROCESSING Data collection will begin once specific patients have been identified to test the device. Initial data gathered will include details such as level of amputation, handedness, and lingering effects like phantom pain and nerve sensitivity. Additional information regarding the patientâ&#x20AC;&#x2122;s mentality about their missing digit(s) and new prosthetic device will be gathered before and after fitting. This information will help the team understand the target population better and allow for more efficient device development in the future. Post-fitting, we will analyze the utility of the prosthetic. Patient feedback regarding comfort, fit, durability and aesthetics will be recorded. We will also analyze the ability of the patients to perform certain tasks such as grasping everyday objects like pencils, soda cans and keys, and their ability type on a keyboard. Data will be gathered using the DASH (Disabilities of the Arm, Shoulder, and Hand) scoring system. Followup data collection, using DASH, can occur at predetermined intervals of 2 weeks and 4 weeks post-delivery to see if there has been improvement over time.

RESULTS The rapid prototyping enabled by 3D printing allows this device to be under continuous development and improvement. Further analysis of comfort, fit, durability and function are ongoing.

End-stage prototypes have been produced with less than $5 of materials. One view of the device is shown in Figure 1. There is potential for this device to be a highly functional, low cost alternative for thumb amputees, especially when thumb reconstruction is not an acceptable option. Instead of having each device custom-made, one might produce the technology for a generic design that can be available in fixed sizes to cut down on delivery time to the end user.

DISCUSSION FDM 3D printing has created new options for prosthetic devices, such as our team's culturally

appropriate, low cost, functional prosthetic device for thumb amputees. Future adaptations could include designs for partial hand amputees or individuals with congenital defects of the hand.

Additionally, a device with moving parts could provide another degree of freedom of flexion at the distal end of the thumb.

REFERENCES [1] Shale CM, Tidwell III JE, Mulligan RP, Jupiter DC, Mahabair RC. A Nationwide Review of the Treatment Patterns of Traumatic Thumb Amputations. Annals of Plastic Surgery. June 2013 Vol 70(6): 647-51.

[2] Spiess AM. (2016, Nov 29). Personal interview.

Figure 1:

[3] Naked Prosthetics. (2017, Jul 26). Phone interview ACKNOWLEDGEMENTS Acknowledgements: We would like to thank Dr. Alexander Spiess, the Swanson School of Engineering and the Office of the Provost at the University of Pittsburgh for providing the funding for this project. Additionally, we would like to thank the Rochester e-NABLE Lab at Vertus High School in Rochester, NY for providing the facilities and resources required for 3D printing and Melvin Cruz for his expertise and mentorship.

CO-REGISTRATION OF IN-VIVO AND EX-VIVO HUMAN MRI BRAIN IMAGES Shane D. McKeon1, Anusha Rangarajan1, Minjie Wu2, Nadim Farhat1, Tales Santini1, Sossena Wood1, Tamer Ibrahim1,3, Milos Ikonomovic4, Julia Kofler5, Oscar Lopez3,6, Bill Klunk2,6, Howard Aizenstein1,2.

1 Departments of Bioengineering, 2Psychiatry, 3Radiology, 4Neurology, 5Pathology and 6UPMC, University of Pittsburgh, Pennsylvania, USA. Email: sdm63@pitt.edu Web: http://www.gpn.pitt.edu/ INTRODUCTION: Alzheimerâ&#x20AC;&#x2122;s disease (AD) is in-vivo scan. In order to make the two scans more the most common form of dementia, affecting comparable we first stripped the in-vivo scan of over five million people in the United States1. the skull using the segmentation function within One of the first neuropathological hallmarks of Statistical Parametric Mapping (SPM12). We AD is the accumulation of amyloid plaques in the reoriented the ex-vivo image into the same brain. Earlier this was detectable only by orientation as the in-vivo image. We then postmortem histology.

However, recent registered the ex-vivo to the in-vivo using an development in in-vivo imaging, allows us to affine transformation in Matlab, which scaled the measure amyloid burden in the living brain. ex-vivo into the in-vivo left hemisphere Correlating amyloid deposition determined by indimensions. The in-vivo half brain was registered vivo scans with ex-vivo histology will provide a to the ex-vivo using FSL (flirt) to obtain an better understanding of the accuracy and optimized alignment. characteristics of the in vivo scan2. Previous studies have used digital photographs of the RESULTS AND DISCUSSION: The initial postmortem brain after slicing to compare with images were very skewed from one another. After in-vivo brain imaging. However, variability in each step of image modification and registration slice thickness and orientation make 3D- volume the alignment became gradually better. reconstruction between the in-vivo MRI and exOverlaying the original in-vivo brain and the revivo histology samples difficult. Obtaining an orientated ex-vivo produces poor alignment, as additional postmortem, ex-vivo MRI of the the ex-vivo still needed to be scaled to the in-vivo formalin-fixed brain could potentially improve scan. When the ex-vivo scan was scaled down the registration.

However, developing the and registered to the in-vivo, the alignment registration methodology must account for the improved but was still insufficient (Figure 1A). time gap between the in-vivo and postmortem The most successful alignment came after using MR scans creating structural discrepancies, the Matlab affine transformation and the FLIRT geometrical deformation due to dehydration, and registration. The products of the two were MR signals that are negatively affected by the overlaid to produce the image in Figure 1B. As reduced proton density within fixed tissue2,3. This seen in Figure 2, each orientation of both the inintermediate ex-vivo MRI could bridge the time vivo andOriginal the in-vivo ex-vivo images are visually similar.

Original in-vivo brain and brain and Coregistered in-vivo brain scaled ex-vivo (Flirt) and scaled ex-vivo gap and will allow for a 3D image in the same resized ex-vivo A B C MR space as the in-vivo MR structural image.

B A Using the ex-vivo MRI, we aim to improve the alignment of the in-vivo MRI to the histological samples through an automated co-registration process. This study focuses on the registration step between the in-vivo and ex-vivo brain.

Figure 1: A. The original in-vivo (green) MATERIALS AND METHODS: A whole overlaid with the Matlab registered ex-vivo brain in-vivo and left hemisphere ex-vivo MRI through affine transformation (red). B. The scan of the formalin-fixed brain were obtained FSL registered in-vivo (green) overlaid with from the same subject to develop a registration the Matlab registered ex-vivo (red) method. The original images showed that the exvivo scan needed to be oriented and scaled to the

1

5

2

3

4

6

Figure 2: 1. In-vivo sagittal 2. Ex-vivo sagittal 3.

In-vivo transverse 4. Ex-vivo transverse 5. Invivo coronal 6. Ex-vivo coronal

CONCLUSIONS: Qualitatively we have concluded that affine registration provided an optimal alignment between in-vivo and ex-vivo

MRI scans. This is an exploratory study and the steps described will need to be repeated on multiple subjects.

ACKNOWLEDGEMENTS: The Swanson School of Engineering, the Office of the Provost, and Dr. Aizenstein for providing me with funding to complete this research. As well as funding from NIH grants R01 MH111265 and P01 AG025204.

REFERENCES: 1. Alzheimerâ&#x20AC;&#x2122;s Association. 2016. http://www.alz.org/facts/overview.asp 2. T. S. Kim et al. IEEE Transactions on Nuclear Science. 47, no. 4, pp. 16071613, Aug 2000.

3. M. Singh et al. 2006 IEEE Nuclear Science Symposium Conference Record, San Diego, CA, 2006, pp. 1982-1985.

4. K. Miller et al. NeuroImage. 57. 167181. 2011.

CORRECTION OF GIBBS RINGING ARTIFACT IN DW-MRI WITH BIOMIMETIC BRAIN PHANTOM AS GROUND TRUTH Katherine R. Rohde Schneider Laboratory, Department of Bioengineering University of Pittsburgh, PA, USA Email: krr74@pitt.edu, Web: www.lrdc.pitt.edu/schneiderlab/ INTRODUCTION Diffusion-weighted magnetic resonance imaging (DW-MRI) is an area of intense study in brain mapping (e.g. over 8000 PubMed entries).

However, the method also exhibits a strong Gibbs ringing artifact that distorts its results. Gibbs ringing occurs as a result of the truncated Fourier transforms used to reconstruct the MR signals into images. When the signal intensity changes drastically – such as near the boundary of tissues – the truncation results in oscillations. In the MR image, this ringing manifests as multiple fine parallel lines adjacent to high-contrast interfaces, such as the corpus callosum (CC). Gibbs ringing has also been shown to skew mean diffusivity (MD) and fractional anisotropy (FA) readings [1].

Previous studies investigating Gibbs ringing correctional algorithms have not included a ground truth measurement, as the true values of the DWMRI image are unknown. Numerical models have been implemented, but these investigations still rely mostly upon qualitative image analysis. This study seeks to quantify the effectiveness of Gibbs ringing correctional algorithms through the use of a physical brain phantom acting as ground truth.

METHODS Two correctional methods were analyzed: Gaussian filtering (GF) and Local Subvoxel-shifts (LS). GF is a non-uniform low-pass filter that yields a smooth transition at the cutoff frequency; it is the most commonly used method to diminish Gibbs ringing [1]. LS removes Gibbs ringing via a re-sampling of the image such that the source of the ringing pattern, the sinc-function, is sampled only at zero crossings [2].

Ground truth was provided by the biomimetic brain phantom constructed by the Schneider Laboratory [3]. The phantom is composed of 20 chambers of hollow polypropylene yarns that mimic human

white matter axons. The chambers are divided by axon density (12.5%, 25%, 50%, 100%) and chamber area (4.0mm2, 16mm2, 36mm2, 64mm2, 100mm2). Graphically, MR signal readings are expected to be constant over uniform density chambers. Phantom DW-MRI data was acquired on a Siemens Magnetom TrioTim MR scanner, with bvalues ranging from 0 to 5000 s/mm2. The spatial frequency domain of each chamber was obtained via the Fourier transformation. Further analysis was completed by calculating the DTI pipeline map of the phantom data, including MD and FA values.

For comparative visual analysis, correctional methods were also tested on DW-MRI data from five healthy subjects acquired on a Siemens Magnetom Trio (3T) MR scanner, with b-values ranging from 0 to 7000 s/mm2.

DATA PROCESSING For each chamber, a voxel interval x along the xaxis was manually determined over which MR signal readings were expected to be constant. The coefficient of variation (CV) over interval x was calculated for each chamber for the original, GF, and LS data sets in the spatial domain. The “expected” constant signal over interval x was also calculated by averaging the MR signals measured for the original, GF, and LS data sets. In the frequency domain, the median percent difference from the expected data was calculated from the percent difference for each frequency measured.

RESULTS Gibbs ringing was identified in the original DWMRI human data, most notably surrounding the CC. Visually, GF only partially reduced the artifact and also contributed to a lower spatial resolution, leading to the loss of fine anatomical details. LS more successfully eliminated the artifact, with less spatial resolution loss. Figure 1 below displays a typical representation of the DW-MRI data before

and after the correctional methods were applied with a zoomed detail (red square) on the CC. Gibbs ringing is indicated by red arrows, and loss of spatial resolution is indicated by a yellow arrow.

Table 1 below displays the mean and SD values of MD and FA for the phantom chamber of area 100mm2 and 100% axon density. On average, GF and LS decreased MD by 1.26% and 0.64%, and decreased FA by 12.15% and 5.55%, respectively.

Previous studies have shown that Gibbs ringing increases FA values, so the significantly reduced FA values for GF and LS is expected [1]. Both methods also decreased SD for both MD and FA, possibly indicating increased precision.

DISCUSSION Visually, LS appears to outperform GF in eliminating Gibbs ringing in the DW-MRI image without introducing dramatic spatial resolution loss.

However, the artifact is still present in the phantom data after LS is applied (shown in Figure 2), indicating that visual analysis alone is insufficient in evaluating the effectiveness of Gibbs ringing correctional algorithms. In the phantom tests, GF reported the lowest CV over interval x, and most closely followed the expected curve in the frequency domain.

Figure 1: DW-MRI data before and after correctional methods with zoomed detail (red square) on the CC. Gibbs ringing is identified by red arrows in the Original and GF images. The yellow arrow indicates loss of anatomical detail in the GF image.

Figure 2 below displays a typical representation of the phantom data in both the spatial domain and frequency domain before and after the correctional methods, as well as the expected MR signal. In the spatial domain, the characteristic oscillations of Gibbs ringing can be clearly identified. The original data exhibited an average CV of 15.2% over interval x, which decreased to 11.3% and 13.7% after GF and LS, respectively. In the frequency domain, the average median percent difference from the expected curve was calculated as 45.0% for the original data, which decreased to 28.6% and 37.3% after GF and LS, respectively.

This study is still limited in scope, as the true MD and FA values are unknown. Further studies using a Monte Carlo simulation are necessary in order to fully quantify Gibbs ringing correctional algorithms. Furthermore, other correctional algorithms such as Total Variation and Total Generalized Variation should also be investigated.

REFERENCES 1. Veraart et al. Magn Reson Med 76.1, 301-314, 2016.

2. Kellner et al. Mang Reson Med 76.5, 1574-1581, 2016.

3. Guise et al. ACS Appl. Mater. Interfaces 8.44, 29960-29967, 2016.

ACKNOWLEDGEMENTS This research was funded by the Swanson School of Engineering and the Office of the Provost. Dr. Walter Schneider and Sudhir Pathak of the Schneider Lab provided resources and guidance.

Figure 2: Spatial and frequency domains of phantom DW-MRI signal (b = 0 s/mm2) over a chamber of area 64mm2 and 50% axon density. DW-MRI signal is expected to be constant over interval x.

Table 1: MA and FA Values over Phantom Chamber of area 100mm2 and 100% axon density MD (Âľm2/ms) b-value: Original GF LS

1000 2.245 2.225 2.231

Mean 3000 1.051 1.037 1.045

5000 0.652 0.642 0.648

1000 0.720 0.665 0.691

FA SD 3000 0.236 0.221 0.229

5000 0.130 0.121 0.126

1000 0.367 0.328 0.349

Mean 3000 0.266 0.236 0.252

5000 0.217 0.185 0.203

1000 0.264 0.265 0.262

SD 3000 0.179 0.177 0.175

5000 0.139 0.134 0.134

Investigating Wheelchair Seating Parameters and Their Effect on Ramp Propulsion Andrew Sivaprakasam, Sarah Bass, BS, Deepan Kamaraj, MD, MS, Alicia Koontz, PhD, RET Human Engineering Research Laboratories University of Pittsburgh, PA, USA Email: sivaprakasam@pitt.edu, Web: http://herl.pitt.edu/ INTRODUCTION Ultralight manual wheelchair users must rely completely on their upper body muscles and joints to transport themselves efficiently. This puts a larger amount of strain on their wrist, elbow, and shoulder joints due to the high demand they are exposed to on a regular basis. Ramps and inclined surfaces are among variations in terrain that add to the challenge. It has been shown that propulsion effort increases as a function of slope [1-3]. These findings imply that ramp propulsion is highly demanding and likely increases the risk of developing upper limb injury. When a person receives a new wheelchair, it is typically configured to reduce propulsion effort on level surfaces by shifting the center of gravity rearward over the rear wheels however this configuration may not be optimal for ramps because the center of gravity shifts further back making it become tippy or unstable. One idea that has the potential to decrease the required propulsion effort is to design a wheelchair that allows the user to modify the configuration ‘on the fly’ to make the system more stable before ascending a ramp. This would provide a quick and convenient way for wheelchair users to prevent or delay the onset of upper body overuse injuries.

Potential modifiable configuration parameters include the overall length and position of the footrest and seat relative to the rear wheel axle, respectively known as the footprint and seat position. The goal of this study was to investigate how changing the wheelchair footprint and seat position may improve ramp propulsion ability. A setup that increases wheelchair stability on a ramp would hypothetically allow propulsion at higher velocities without increases in cadence.

METHODS Subjects: Participants were eligible if they had a spinal cord injury, were at least 1 year post-injury or diagnosis, used a manual wheelchair for majority of mobility (40+ hours/week), and were over 18 years of age. Participants were unable to participate if

they had upper limb pain or injury that interfered with their ability to propel, had cardiopulmonary disease, or were unable to fit the study wheelchair.

Experimental Protocol: An ICON (Slidell, LA) A1 wheelchair was adjusted to match measurements taken from each participant’s wheelchair. A wheel instrumented with a SmartWheel (Three Rivers Holdings, Mesa AZ) was attached to each participant’s non-dominant side of the chair, while a wheel with matching inertial properties and tread was attached to the dominant side to maintain symmetry. The SmartWheel measured forces, moments, and velocities at 100 Hz occurring at the handrim of the wheelchair.

Participants completed propulsion tasks on a Computer Assisted Rehabilitation Environment (CAREN) system. The CAREN system includes a six degree-of-freedom motion platform with an embedded dual treadmill surrounded by a virtual reality screen and a 10-camera VICON (Vicon Peak, Lake Forest, CA) motion capture system.

The ICON wheelchair was altered to investigate four different wheelchair configurations: seat anterior/short footprint (AS), seat anterior/long footprint (AL), seat posterior/short footprint (PS), and seat posterior/long footprint (PL). The treadmill speed was adjusted automatically using real-time motion capture data, allowing participants to set their own pace down a virtual path on three different levels of incline: 0, 3, and 6 degrees.

DATA PROCESSING SmartWheel forces, moments, and velocities were processed using a 4th order Butterworth filter with a cutoff frequency of 20 Hz. The push phase of each propulsion cycle was identified using a custom Matlab program that uses the recorded moment about the axle of the rear wheel to determine the start and end of each stroke. Ten cycles were selected for analysis after participants achieved a steady propulsion rate. Cadence was calculated using ten divided by the time taken in each trial to

complete the ten analyzed cycles. Velocity was averaged over the same period. A two-way, repeated measures ANOVA was computed in SPSS version 23 (IBM) to determine significance of the results and investigate the observed differences in participant cadence and velocity between inclines and configurations.

RESULTS Seven manual wheelchair users (36.9 ±10.2 yrs, 1 female) with varying levels of spinal cord injury were recruited for this study. Based on cadence and velocity, participants’ performances on each of the three inclines were not affected significantly by changing the configuration, though the AS and PS configurations had slightly higher average velocities compared to the other two configurations (Tables 1 and 2). A significant decrease in cadence was found in the AL configuration between 3 and 6 degree inclines (p=0.017). In the PS configuration, a significant decrease in velocity between 3 and 6 degree inclines was also observed (p=0.024). No significant differences in cadence or velocity were found in the AS and PL configurations between the tested inclines.

DISCUSSION These findings may indicate that participants found the difference between the 3 and 6 degree inclines more noticeable or difficult in the PS and AL configurations than in the AS and PL configurations. This suggests AS and PL configurations allow for more consistent propulsion across different incline levels. The PS configuration is the least stable of the four conditions, which may explain the significant decrease in velocity at higher

inclines. The AL configuration theoretically has the highest stability and enabled participants to ascend the steeper ramp using a lower cadence. Because high cadence has been linked to poor median nerve health, reducing cadence during propulsion can reduce the risk of developing carpal tunnel syndrome [4]. Our findings overall suggest that having a more unstable wheelchair setup on the ramp can have a negative consequence on ramp speed and that there may be some benefit to increasing wheelchair stability ‘on the fly’ for reducing the number of strokes needed to ascend a steep ramp.

REFERENCES 1. Hurd WJ, et al. Official Journal of the International Society of Electrophysiological Kinesiology, 19, 942-947 2009.

2. Morrow MM, et al. Official Journal of the International Society of Electrophysiological Kinesiology, 20, 61-67 2010.

3. Koontz AM, et al. Journal of Rehabilitation Research and Development, 42, 447-458 2005.

4. Boninger M, et al. Archives of Physical Medicine and Rehabilitation, 80, 910-915 1999.

ACKNOWLEDGEMENTS This project would not be possible without the support of Dr. Koontz and her graduate students. I would also like to acknowledge the Swanson School of Engineering and Office of the Provost and Human Engineering Research Laboratories, and the VA VISN Center Pilot Project Program for funding this project. The contents of this abstract do not represent the views of the Dept. of Veterans Affairs or U.S. Government.

Tables 1 and 2: Mean velocities and cadences of participant trials in four configurations and three levels of incline (significant within-configuration differences highlighted in yellow) Measure Velocity

Configuration AS

AL

PS

PL

Slope Level 3 deg 6 deg Level 3 deg 6 deg Level 3 deg 6 deg Level 3 deg 6 deg

Mean 1.31 1.069 0.717 1.183 0.72 0.695 1.404 1.106 0.772 1.523 0.895 0.504

Std. Error 0.106 0.212 0.166 0.183 0.175 0.145 0.143 0.19 0.202 0.137 0.129 0.192

Measure Cadence

Configuration AS

AL

PS

PL

Slope Level 3 deg 6 deg Level 3 deg 6 deg Level 3 deg 6 deg Level 3 deg 6 deg

Mean 1.194 1.293 1.12 1.195 1.242 1.093 1.295 1.353 1.151 1.163 1.121 0.944

Std. Error 0.133 0.196 0.215 0.162 0.189 0.175 0.091 0.189 0.201 0.124 0.166 0.251

Nanomolar Drag Reducing Polymers (DRPs) Reduce Near-wall Margination of Rigid RBCs in Microchannels: A Potential Therapy for Sickle Cell Disease (SCD) Dan Crompton, B.S.1,2, Shushma Gudla1,2, Marina V. Kameneva, PhD1,2,3 1 Department of Bioengineering, 2 McGowan Institute for Regenerative Medicine, 3 Department of Surgery, University of Pittsburgh, PA INTRODUCTION Sickle cell disease (SCD) is a genetic disorder caused by a mutation in the β-globin gene where abnormal hemoglobin polymerizes under hypoxic conditions, causing red blood cells (RBCs) to convert into rigid or â&#x20AC;&#x2DC;sickledâ&#x20AC;&#x2122; cells [1]. Sickled RBCs (S-RBCs) more readily adhere to endothelial cells and cause sudden vaso-occlusions, leading to severe pain and tissue necrosis. These SCD complications are related in part to the FĂĽhraeus effect, where normal deformable RBCs tend to move toward the blood vessel center, leaving less or non-deformable cells such as S-RBCs to marginate at vessel walls and become more likely to enter daughter branches at vessel bifurcations.

This creates a normal deformable RBC concentrated core and a near-wall cell attenuated layer known as the â&#x20AC;&#x2DC;cell-freeâ&#x20AC;&#x2122; layer (CFL) in microvessels and microchannels [2]. (a) Healthy bovine RBCs and (b) heat treated bovine rigid RBCs are subjected to 0s-1 (top) and 1000s-1 (bottom) shear rates Previous work performed by this laboratory has shown that the addition of nanomolar concentrations of blood-soluble DRPs causes healthy RBCs to evenly distribute across microchannels and significantly reduces the width of the CFL [3,4]. We hypothesize that the addition of DRPs in suspension of normal and rigid RBCs (like those in SCD crisis) will result in even rigid RBC distribution across microvessels and decrease the traffic of rigid RBCs into bifurcations; thereby, potentially decreasing the incidence of vaso-occlusion and reducing pain and tissue damage experienced by SCD patients.

METHODS Fresh bovine RBCs were washed, leukoreduced and suspended at 30% hematocrit in solution of 6% bovine serum albumin (BSA) in phosphate buffered saline (PBS). Half of the suspended RBCs were then rigidified at 52°C for 30 minutes, and pooled together with the untreated half to create 50% healthy and 50% rigid RBC mixtures by volume.

Suspensions, both with and without 10 ppm of the DRP polyethylene oxide (PEO), MW 4,000 kDa, were driven at 5.9 đ?&#x153;&#x2021;L/min (max shear rate: 1200 s-1, Reynolds number <1.5, pressure drop ~6 mmHg) (n=6) through a bifurcating PDMS microchannel (Figure 1). Samples were collected from main and branch outlets for analysis.

Figure 1 : PDMS microchannel Main dimensions: 10,000(l) x 200(w) x 50(h) đ?&#x153;&#x2021;m & Branch dimensions: 4,300(l) x 100(w) x 50(h) đ?&#x153;&#x2021;m

DATA PROCESSING Samples collected from main and branch outlets were analyzed on a Linkam Shearing Stage (Linkam Scientific, UK) at shear rates of 0 and 1000 s-1 (Figure 2). Individual cells were determined to be either â&#x20AC;&#x2DC;healthyâ&#x20AC;&#x2122; or â&#x20AC;&#x2DC;rigidâ&#x20AC;&#x2122; based on deformation under shear using a logistic regression algorithm.

The percent change of healthy and rigid cells exiting through branch outlets between control and experimental runs was calculated and normalized by healthy RBC hematocrit. A one tailed t-test (a= 0.05) was used to determine if percent differences were statistically significant.

Figure 2: (a) Healthy bovine RBCs and (b) heat treated bovine rigid RBCs are subjected to 0s-1 (top) and 1000s-1 (bottom) shear rates. Healthy RBCs exhibit substantial deformation, whereas rigidified RBCs show little to no deformation.

RESULTS In control groups (no DRP), an average of 5% Âą 2.3% fewer normal RBCs exited the branch outlet than rigid RBCs due to the margination of rigid RBCs, while in experimental groups (with DRP) an average of 6% Âą 4.3% more normal RBCs exited the branch outlet than rigid RBCs (n = 6, p = 0.00168) (Figure 3).

Figure 3: Addition of DRPs increased number of healthy RBCs exiting branch outlet by 11%

DISCUSSION A statistically significant difference in the number of rigid RBCs entering branch outlets with the presence of DRPs indicates that DRPs caused both healthy and rigid RBCs to become more evenly distributed across the microchannel. An increase in near-wall healthy RBC concentration along with a decrease in near wall rigid RBC concentration allowed more healthy RBCs to enter branch vessels and decreased the probability of rigid cells entering branch vessels.

Reduced non-deformable and increased deformable RBC traffic to smaller branches by over 10% demonstrates the potential to decrease instances of vaso-occlusion in SCD patients if given a nanomolar

concentration of blood soluble non-toxic DRPs, which can significantly improve the quality of life for SCD patients.

Current studies gathering data from two generations of bifurcations which decrease from a 200 đ?&#x153;&#x2021;m width to 100 đ?&#x153;&#x2021;m and then to 50 đ?&#x153;&#x2021;m using similar techniques are ongoing. In our future studies, we expect to see amplified positive effects in the distributions of normal and non-deformable RBC after passing multiple bifurcations. This would allow a lower number of sickled cells to reach the smallest arterioles and capillaries and will lead to a novel therapy for patients with SCD. REFERENCES 1] Rees, D.C., Williams, T.N., Gladwin, M. T. Sickle-cell disease. The Lancet, 376, 2018-2031, 2010.

[2] FĂĽhraeus, R. The suspension stability of the blood. Physiological Reviews, IX, 241â&#x20AC;&#x201C;275, 1929.

[3] Kameneva, M.V., Wu, Z.J., Uryash, A., Repko, B. et al., Blood soluble drag-reducing polymers prevent lethality from hemorrhagic shock in acute animal experiments, Biorheology, 41, 53â&#x20AC;&#x201C;64, 2004.

[4] Marhefka, J. N., Zhao, R., Wu, Z. J., Velankar, S. S., Antaki, J. F., & Kameneva, M. V. Drag reducing polymers improve tissue perfusion via modification of the RBC traffic in microvessels. Biorheology, 46, 281â&#x20AC;&#x201C;292, 2009.

ACKNOWLEDGEMENTS Prithu Sundd, PhD Jonathan H. Waters, MD Katrina Zougari, B.E. Luke Zeigler , B.S. Swanson School of Engineering Office of the Provost