College of Engineering

Kathrina Waugh

College of Engineering Computer Engineering

Faculty Mentor: Dr. Baris Taskin

Electrical & Computer Engineering

Ragh Kuttappa Co-Mentor

Exploiting Energy Efficiency via Charge Recovery Logic

A plethora of electronic systems are powered by batteries and reducing the power consumption is beneficial to increasing battery life. Low power VLSI design has become the core focus of circuit design to reduce power consumption. However, as researchers attempt to lower power dissipation, there is an evident risk that lower power dissipation limits the overall performance. Subsequently, power and energy consumption, with speed, are now the most critical design parameters for electronic systems design. Most recently, charge recovery logic (CRL), has gained interest for low power applications that demonstrates high energy-efficiency via energy recycling compared to that of CMOS while operating at high speeds in the GHz ranges. To do this, CRL employs a sinusoidal signal that provides both energy and timing for the logic gates. Statistically, there are significant power savings of 82% between a CRL inverter and a CMOS inverter: A CRL inverter consumes 215μW whereas a CMOS inverter consumes 1178μW. This project explores the design automation of the circuit layout, for both CMOS and CRL circuits while addressing the future needs of design scalability and diminishing transistor sizes.

College of Engineering

Yu-Chieh (Jamie) Wu

College of Engineering

Engineering Technology

Faculty Mentor: Dr. Richard Chiou

Engineering Technology

Building a robotic 3D scanner and sortation system

Robots are often used to automate dangerous and/or repetitive tasks in manufacturing industries. These systems usually deal with mass production and need to pick and place products to different locations for further processing and shipping. Such labour intensive tasks can be manual, semi-automated or fully automated. This research seeks to understand and build a fully automated environment integrated with a 3D scanner system on a small scale. A product would first be picked up by a 6-axis robotic arm and placed onto a rotating table. A sensor would then scan the product and translate its analog output data for 3D plotting purposes. In this case, an infrared sensor is preferred to an ultrasonic or LIDAR sensor as the infrared sensor yields the most accurate readings for short distances. The devices are controlled by Arduino and the data collected will generate a 3D point-cloud plot using MATLAB. A fully automated, 3D scanner system will significantly reduce labour costs, increase efficiency and accuracy, and maximize the utilization of space in a factory.

College of Engineering

Abhigyan Khullar

College of Engineering

Electrical Engineering

Faculty Mentor: Dr. Yury Gogotsi

Materials Science & Engineering

Dr. Xuehang Wang Co-Mentor

Enhancing Performance of MXene Supercapacitors in Highly Saturated Neutral Aqueous Electrolytes

The world needs portable devices that can store more electrical energy with fast charging rate. Higher charging speed allow electrochemical energy storage (EES) device to be fully charged in minutes while high energy storage capability extends battery life. A Supercapacitor is an EES device known for their, high power output and safety, but it has a low energy density compared to a battery. Recently, a two-dimensional nanomaterial, known as MXene has shown a high volumetric capacitance and high rate capability due to its highly conductive and layered structure. Currently MXene supercapacitors have limited storing capability as it uses corrosive electrolytes. Our research aimed to substitute the corrosive electrolytes with saturated neutral aqueous electrolytes. Effectively reducing corrosion to the device, improve its safety and extending the voltage window, allowing for more energy storage. We used electrochemical tests, to test the performance of electrolytes, such as Lithium TFSI and Lithium acetate. A larger voltage window was observed using the saturated LiTFSI compared to diluted aqueous electrolyte, however, the results also indicated a salt dependent change in voltage window.

College of Engineering

Christina Strobel

College of Engineering

Electrical Engineering

Faculty Mentor: Dr. Yury Gogotsi

Materials Science & Engineering

Simge Uzun Co-Mentor

Developing Conductive MXene Yarns for Smart Textile Applications

Research exploring conductive yarns can push the future of seamless wearable technology. These yarns allow for various applications, including energy harvesting and storage and electromagnetic interference shielding. Here, the yarns are made using a highly conductive nanomaterial, Ti3C2 MXene. The desirable properties of MXenes for smart textile applications are high conductivity, electrochemical activity and chemical stability.

To produce conductive yarns, low-cost, natural yarns including fine and coarse cotton, bamboo, and linen were dip-coated in a Ti3C2 MXene dispersion. The concentration and flake size distribution were tailored to ensure uniform coating around the individual fibers and yarn. A mass loading of 2 mg/cm was achieved without MXene flaking, and the resistance of the yarns was 5-10 Ω/cm with a conductivity of 250 S/cm. This is within the upper range of conductivity for commercially available conductive yarns. The yarns were knitted by industry size digital knitting machines. Of the four types of yarns knitted, fine cotton and bamboo produced better knitted samples due to their flexibility. The scalability of this method allows conductive yarns to be cost-effectively produced and knitted on a large scale.