Molecular recognition made of an "adsorbed" carbon nanotubes transducer

ARTICLES PUBLISHED ONLINE: 24 NOVEMBER 2013 | DOI: 10.1038/NNANO.2013.236

Molecular recognition using corona phase complexes made of synthetic polymers adsorbed on carbon nanotubes Jingqing Zhang1‡, Markita P. Landry1‡, Paul W. Barone1‡, Jong-Ho Kim1,2‡ et al.* Understanding molecular recognition is of fundamental importance in applications such as therapeutics, chemical catalysis and sensor design. The most common recognition motifs involve biological macromolecules such as antibodies and aptamers. The key to biorecognition consists of a unique three-dimensional structure formed by a folded and constrained bioheteropolymer that creates a binding pocket, or an interface, able to recognize a specific molecule. Here, we show that synthetic heteropolymers, once constrained onto a single-walled carbon nanotube by chemical adsorption, also form a new corona phase that exhibits highly selective recognition for specific molecules. To prove the generality of this phenomenon, we report three examples of heteropolymer–nanotube recognition complexes for riboflavin, L-thyroxine and oestradiol. In each case, the recognition was predicted using a two-dimensional thermodynamic model of surface interactions in which the dissociation constants can be tuned by perturbing the chemical structure of the heteropolymer. Moreover, these complexes can be used as new types of spatiotemporal sensors based on modulation of the carbon nanotube photoemission in the near-infrared, as we show by tracking riboflavin diffusion in murine macrophages.

M

olecular recognition and signal transduction are the two main challenges in sensor design1,2. Frequently, scientists and engineers borrow from nature to gain analyte specificity and sensitivity, using natural antibodies as vital components of the sensors1,3–6. However, antibodies are expensive, fragile, easily lose biological activity on external treatment (such as immobilization) and exhibit batch-dependent variation, limiting their use in widespread applications1,6,7. This has driven the search for methods to synthesize or discover artificial antibodies or their analogues from polymeric materials, leading to molecularly imprinted polymers6,8 and DNA-aptamers2,3,6.

Single-walled carbon nanotubes (SWNTs), rolled cylinders of graphene, are ideal materials for molecular recognition and signal transduction. They have near-infrared bandgap fluorescence9 with no photobleaching threshold10,11, and are sensitive to the surrounding environment. Electron-donating or -accepting groups can increase or decrease emission12–14 with single-molecule sensitivity15–17. Adsorbates can also screen the one-dimensional confined exciton18,19, causing solvatochromic shifts in emission20,21, particularly with polymer wrappings that change conformation. Our laboratory and others have developed SWNT fluorescence sensors for detecting b-D-glucose12, DNA hybridization21, divalent metal cations20, assorted genotoxins22, nitroaromatics23, nitric oxide13,17, pH16 and the protein avidin14. These efforts have invariably exploited conventional molecular recognition entities, such as enzymes24, oligonucleotides21 or specific functional groups with known affinity for the target molecule13. In this work, we instead demonstrate a new recognition motif consisting of specific polymers adsorbed onto a SWNT, whereby the interface recognizes certain small-molecule adsorbates, resulting in modulation of nanotube fluorescence (Fig. 1). We show that the recognition results from the combination of analyte adsorption to the graphene surface and lateral interactions with molecules in the adsorbed phase in a predictable manner. We introduce this concept as corona phase molecular recognition.

Screening of a polymer–SWNT library To generate polymer–nanotube interfaces in aqueous solution, candidate amphiphilic polymers were synthesized with both hydrophobic and hydrophilic domains, enabling SWNT surface adsorption and entropic stabilization, respectively. For simplicity, only non-ionic or weakly ionic polymer phases were used in this study, to assist structural understanding. For screening, each polymer– SWNT construct was exposed to a library of 36 small molecules, and the resulting SWNT fluorescence response was monitored in triplicate using a near-infrared fluorescence spectrometer, automated to acquire data in a 96-well-plate format (Supplementary Fig. 4). Each spectrum was deconvoluted into eight SWNT chiralities using a custom spectral fitting program (Supplementary section ‘Materials and Methods’) that also calculates standard errors. The resulting intensity and wavelength modulations of each construct before and after the addition of each analyte in the library were recorded (for all unprocessed spectra see Supplementary Figs 23–46).

Molecular recognition by polymer corona phase on SWNTs From the polymer–SWNT library screened to date we identified three distinct examples of polymer–nanotube-mediated molecular recognition. The simplest example is provided by a rhodamine isothiocyanate-difunctionalized poly(ethylene glycol)–SWNT complex (RITC-PEG-RITC–SWNT; Fig. 2a, 5 or 20 kDa), which exhibits fluorescence quenching exclusively in response to oestradiol (both alpha- and beta-oestradiol). Two similar synthetic variants—fluorescein isothiocyanate-difunctionalized PEG (FITC-PEG-FITC; Fig. 2b) and distearyl phosphatidylethanolamine PEG (PE-PEG; Fig. 2c)—result in non-selective response profiles. The simple polymer design allows for elucidation of the adsorbed phase structure. The selectivity of this response (Fig. 2a) is distinct from schemes using principle component analysis22 or differential sensor responses25 for analyte recognition, and we therefore assign

*A full list of authors and their affiliations appears at the end of the paper.

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NATURE NANOTECHNOLOGY Hydrophobic

DOI: 10.1038/NNANO.2013.236

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Figure 1 | Schematic of the molecular recognition concept. a, A polymer with an alternating hydrophobic and hydrophilic sequence adopts a specific conformation when adsorbed to the nanotube. The polymer is pinned in place to create a selective molecular recognition site for the molecule of interest, leading to either a wavelength or intensity change in SWNT fluorescence. b, An example of a hydrophobic–hydrophilic alternating sequence for boronic acidderivatized phenylated dextran.

it as the first demonstration of molecular recognition from the adsorbed phase itself. In the polymer–SWNT complex, the FITC fluorescence is quenched, providing evidence that the hydrophobic ends of the polymer are adsorbed onto the SWNT surface (Supplementary Fig. 8). The hydrophilic PEG chain is expected to form a loop extending into solution. Such a partitioning of hydrophobic and hydrophilic domains is consistent with earlier studies that have utilized PEG-conjugated hydrophobic molecules for SWNT suspension26–32, and is supported by the experimental observation that PEG itself is incapable of suspending SWNTs. Although we do not have direct evidence of the formation of the loop structure, single-molecule fluorescent imaging of the polymer co-localized with the fluorescent SWNT is consistent and further supports both this structure and the interaction of oestradiol with the hydrophobic anchors (Supplementary Figs 9–12, Supplementary Tables 4–6).

This structural configuration is also corroborated by molecular dynamics simulations (Supplementary section ‘Materials and Methods’) for the three polymers (Fig. 2). Oestradiol contains an aromatic group that can adsorb to the SWNT surface if the pendant hydroxyl groups are hydrogen-bonded to the adjacent RITC amides. The molecular weight of the PEG chain does not influence the selectivity (Supplementary Figs 13–15), but the endgroup structure has a substantial effect (Fig. 2a–c). The molecular recognition of the RITC-PEG-RITC–SWNT to oestradiol results from the strong interaction between the oestradiol and RITC anchors. A molecular dynamics simulation at a starting coverage of 50 polymers per 20 nm of SWNT reveals that, at equilibrium, 80% of the SWNT surface is covered by RITC anchors. We conclude that the intermolecular spacing of hydrophobic groups on the SWNT determines selectivity. Different characterization techniques have been applied here: dry-state atomic force microscopy (AFM) estimated a mean radius of 2.5 nm for RITC-PEG-RITC–SWNT, consistent with the 2.7 nm estimated from molecular dynamics 2

results, but smaller than the 8.1 nm that is estimated from singleparticle tracking experiments (Supplementary Table 3). Under the hydrated conditions of single-particle tracking, the hydrodynamic radius can be increased. While AFM provides a direct measure of the complex radius, single-particle tracking can be influenced by the variations in nanotube length. Transmission electron microscopy (TEM) images (Supplementary Fig. 17a) indicate a range of radii from bare surface (0.47 nm) to approximately twice the AFM average value (4.9 nm), reflecting variable surface coverage along the length.

We also compared this with responses obtained from SWNTs suspended with two commonly used dispersing agents. Sodium cholate suspended SWNT (Fig. 2d) is non-responsive to the analytes tested, confirming the tight surface packing reported previously33.

In contrast, d(GT)15 DNA-wrapped SWNT (Fig. 3d) shows poor selectivity, suggesting a more porous interface composed of consecutive DNA helices34. This type of profile, which informs the accessibility of molecules to the SWNT surface, as presented in Fig. 2, allows for a unique ‘fingerprinting’ of polymer adsorbed phases in a manner inaccessible to other analytical techniques such as NMR, Fourier transform infrared (FTIR) spectroscopy and ultraviolet absorption. Structural schematics of the nanotube complexes were deduced from a combination of polymer molecular structure and fingerprinted response profile, further supported by single-particle tracking data and molecular dynamics results (Fig. 2).

A more complex example is provided by the PEG brush described in Fig. 3. One brush segment is alkylated for hydrophobicity while the remaining sites can display a variety of functionalities.

When these sites contain Fmoc L-phenylalanine (Fmoc-PhePPEG8), we find that a seven-membered brush structure recognizes L-thyroxine (Fig. 3a), whereas a three-membered analogue does not (Fig. 3b). Replacing the Fmoc L-phenylalanine with amine groups also results in a loss of selectivity (NH2-PPEG8, Fig. 3c) due to

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surface forces. The recognition is realized only once the polymer and the SWNT are conjugated with each other, while the polymers by themselves have little to no previously identified connection or affinity for the analytes of interest. We designate this effect ‘corona phase’ molecular recognition to highlight the essential role of both the polymer and nanotube surfaces, and we note that comparable spherical and elliptical nanoparticles may also show phases capable of molecular recognition. The observation that binding sites formed in this manner have tunable affinity following small changes in polymer composition and nanotube chirality indicates that the potential parameter space is exceedingly large.

Furthermore, a theoretical framework based on a two-dimensional equation of state provides a quantitative understanding of the library of responses and offers strong mechanistic insight for the recognition. Our work provides a platform that can be used in various fields, such as sensor development, nanoparticle surface science, single-molecule polymer physics and the study of nanoparticle–biomolecule interactions. However, of immediate utility are the families of fluorescent constructs that can be used for realtime, intracellular detection of important biomolecules, as demonstrated experimentally in this work.

Received 17 December 2012; accepted 10 October 2013; published online 24 November 2013

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Acknowledgements The authors thank L. Trudel for her assistance with cell culture. The authors thank D. Wittrup, C. Love and V. Sresht for discussions. This work made use of the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation (grant no. OCI-1053575). M.S.S. acknowledges a grant from the Army Research Office and support via award no. 64655-CH-ISN to the Institute for Solider Nanotechnologies. D.A.H. acknowledges the Damon Runyon Cancer Research Foundation. A.A.B. is funded by the National Defense Science & Engineering Graduate Fellowship. A.J.H. acknowledges funding from the Department of Energy SCGF programme (contract no. DE-AC05-06OR23100). Z.W.U. acknowledges support from the Department of Energy CSGF (DOE grant DE-FG02-97ER25308). M.P.L. acknowledges an NSF postdoctoral research fellowship (award no. DBI-1306229). S.K. was supported by a fellowship from the Deutsche Forschungsmeinschaft (DFG).

Author contributions M.S.S. conceived and developed the recognition concept, with input from P.W.B. and D.A.H. Authors J.Z., M.P.L., P.W.B. and J.K. contributed equally to this work. J.Z., P.W.B. and M.S.S. analysed the data and co-wrote the manuscript, with contributions from S.B.

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International Scholarly Research Network ISRN Nanotechnology Volume 2012, Article ID 102783, 9 pages doi:10.5402/2012/102783

Review Article A CNTFET-Based Nanowired Induction Two-Way Transducers Rostyslav Sklyar Verchratskogo st. 15-1, Lviv 79010, Ukraine Correspondence should be addressed to Rostyslav Sklyar, sklyar@tsp.lviv.ua Received 15 December 2011; Accepted 28 February 2012 Academic Editors: C. A. Charitidis and J. Sha Copyright Š 2012 Rostyslav Sklyar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

A complex of the induction magnetic field two-way nanotransducers of the different physical values for both the external and implantable interfaces in a wide range of arrays are summarized. Implementation of the nanowires allows reliable transducing of the biosignals’ partials and bringing of carbon nanotubes into circuits leading to examination of the superconducting transition.

Novel sensors are based on the induction magnetic field principle, which causes their interaction with an ambient EM field.

Mathematical description of both the signal and mediums defines space embracing of the relevant interfacing devices. As a result, a wide range of the nano-bio-transducers allow both delivering the variety of ionized biosignals and interface the bioEM signals with further stages of electronic systems. The space coverage and transducing values properties of the state-of-the-art magnetic interfaces are summarized, and directions for their future development are deduced.

1. Introduction: Biophysical Signals, Transducing, and Interface Applications A biosensor is a device that incorporates a biologically active layer as the recognition element and converts the physical parameters of the biological interaction into a measurable analytical signal [1]. Understanding of biosignals’ (BS) nature and properties of their mediums are a basis for effective design of magnetic interfaces (MIs). Rapid progress in the advancement of several key science areas including nanoscale interfaces has stimulated the development of electronic sensor technologies applicable to many diverse areas of human activity. For example, the conceptualization and production of electronic nose devices have resulted in the creation of a remarkable new sector of sensor technology resulting from the invention of numerous new types of olfactory-competent electronic sensors and sensor arrays [2].

The growing variety of biosensors can be grouped into two categories: implantable and external. In turn, the last one has two existing paradigms: wearable sensor and noncontact sensor. A wearable sensor had potential to be intrusive, and noncontact sensor methods may still be intrusiveness to a certain extent, while a noncontact sensor is limited in its capability of acquiring physiological signals [3]. Voltage potentials of the living organism and its organs are measured

by both implantable and external electric field probes of high sensitivity [4]. Information on organ activity is obtained by measuring biomagnetic signals. For such purposes a multichannel high-temperature superconducting quantum interference device (high Tc SQUID) system for magnetocardiography (MCG) and magnetoencephalography (MEG) of humans, with high magnetic field resolution, has been developed [5, 6].

The most current sensing devices give us the possibility to receive a full scale of both the internal and external control BS. The internal ones are picking up by polymeric microprobes, CMOS chips, and nanoneedles, while the external by electromyography and neuroprosthetic (electroencephalogram (EEG) and MEG) systems. Improving an informational capability of the interface is implemented by the application of the advanced superconducting transducer and electromagnetic (EM) transistor/memristor [7, 8]. These elements are arranged into the arrays of a different configurations and can cover the order of spaces from macro- to nanolevels.

There are a number of methods and devices for transducing different BS into recordable or measurable information.

The transfer of nerve impulses (NI) is the main data flow that carries sensory information to the brain and control signals from it and from the spinal cord to the limbs.

2 Moreover, the complex view on BS requires further stages of precise processing in order to decode the received or control information. There are different kinds of transducers/sensors for picking up NI: room-temperature and superconducting, external, and implantable. Development of such devices is increasing the penetration into bioprocess while simultaneously simplifying the exploitation of the measuring systems in order to bring them closer to the wide range of applications. For this reason, the magnetometer with a room-temperature pickup coil (PC) for detecting signals, which can clearly be detected in higher frequency range, was developed in order to simplify the SQUID system. The PC is set outside the cryostat and is connected to the input coil of the SQUID [9] or a channel of superconducting field-effect transistor (SuFET) [10]. On the other hand, implantableinto-nerve fiber transducers are evolving from the ordinary Si-chip microelectronics devices [11] into superconducting and nanodevices [12, 13].

The recent achievements in nanoelectronics can be regarded as a further step in the progress of BS transduction.

They give us the possibility to create the most advanced and universal device on the basis of known microsystems.

Such a sensor/transducer is suitable for picking up BS— NI, electrically active (ionized) molecules, and the basepair recognition event in DNA sequences—and transforming it into recognizable information in the form of electric voltage, or a concentration of organic or chemical substances.

Moreover, this process can be executed in reverse. Substances and/or voltages influence BSs, thereby controling or creating them (BS) [14]. Steady and rapid progress in the robotics field requires ever quicker and better human-machine interaction and the development of a new generation of interfaces for intelligent systems. Such advances give rise to markedly increased biophysical research on the one hand and the need for new bioelectronic devices on the other. Transduction and measurement of BS are key elements of MIs design.

There are two means involved in signal transduction: (1) biochemical—by hormones and enzymes; (2) biophysical— by nerve impulses (ionic currents). Let us consider the biophysical ones as useful for the said interfaces design above.

There are two values—voltage and electric current—which characterize the pathway of transduction [15].

Calculations of PC arrays were performed with the primary sensor flux transformer sites distributed uniformly on a spherical sensor shell, extending from the vertex to a maximum angle max [16]. The radial magnetometers and gradiometers occupy one site each, there are two orthogonal planar gradiometers at each site and there are three orthogonal magnetometers at each site for vector magnetometers. Coverage can be achieved by designing some kind of density control mechanism, that is, scheduling the sensors to work alternatively to minimize the power wastage due to the overlap of active nodes’ sensing areas. The sensing area of a node is a disk of a given radius (sensing range). The sensing energy consumption is proportional to the area of sensing disks or the power consumption per unit [17].

There are two broad ways of brain-computer interface (BCI): invasive and noninvasive. The invasive technique can capture intracortical action potentials of neurons and thus,

ISRN Nanotechnology provides high signal strength spatiotemporally, for example, prediction of movement trajectory. In noninvasive technique, EEG and MEG have emerged as viable options; both of them have time resolutions in milliseconds. Any activity in brain is accompanied by change in ionic concentrations in neuron leading to polarization and depolarization. Such an electrical activity is measured by EEG, while MEG measures the magnetic field associated with these currents. Electric and magnetic fields are oriented perpendicular to each other [18].

Application of organic-, chemical-, and carbonnanotubes- (CNT-) based FETs for design of the superconducting transducers (SuFETTrs) of BS into different quantities (electrical and biochemical) is the proposed variant of interfacing [19]. The placement of the devices can be carried out both in vivo and in vitro with the possibility of forming the controlling BS from the said quantities. The range of picked up BS varies from 0.6 nA to 10 µA with frequencies from 20 to 2000 Hz. A further step should be the synthesis of the said two methods in order to develop the internal (implantable) nano-bio-interface arrays. This means wrapping of molecular nanowired PC around the axons of a nerve fibre or synapses of neurons in order to obtain the natural biosignals from the nervous system and brain. This leads to sensing access across a vast range of spatial and temporal scales, including the ability to read neural signals from a select subset of single neural cells in vivo. Moreover, this process can be executed in reverse for introducing the artificial control signals with the local neural code into the single cell electrical activity.

2. Biosignals and Nanoelements for Their Transduction As an electrical signal, the biosignal has two components: electrical potential or voltage and ionic or electronic currents. The first component is sufficiently developed and does not require penetration into the substances of biosignal propagation. The marketable progress in transducing of the second component began when the necessary instrumentation for measurement of micro- and nanodimensions had been created [14].

Short platinum nanowires (NWs) already have been used in submicroscopic sensors and other applications. A method of making long (cm) Pt NW of a few nanometers in diameter from electrospinning was described [20]. Those wires could be woven into the first self-supporting webs of pure platinum. Double-gated silicon NW structures (DGSiNW), where the position and/or type of the charge could be tuned within the NW by electric field, have been studied [21]. Self-assembled molecular nanowires were found to be composed of a single crystal, allowing good electrical transport with low resistivity [22].

An interesting structure is that of helical CNT or nanocoils for PCs. Nanocoils offer unique electronic properties that straight CNT do not have. The plasticity of CNT will be relevant to their use in nanoscale devices [23].

Carbon nanocoils (CNCs), as a new type of promising

ISRN Nanotechnology nanomaterials, have attracted considerable attention because of their potential applications, such as parts for nanoor micro-electromechanical systems, EM wave absorbers, reinforced composites, nanosolenoids, and field emission devices [24] Integrated CMOS image sensor device for in vivo neural imaging has been developed. Improvement in the packaging process has resulted in a compact single-chip device for minimally invasive imaging inside the mouse brain [25]. Application of the SuFET’s modifications such as CMOSuFET (low Tc ) [26] and coplanar SuFET (high Tc ) [27] broadens the range of requirements, which are being satisfied by the SuFETTr. Alternatively, an FET-based neurotransducer with CNT or PC kind of input circuit for the nerve and neuron impulse has been designed. A CNTFET with a high-temperature superconducting channel is introduced into the nerve fibre or brain tissue for transducing their signals in both directions [28].

Flexible antennas have the potential to enhance the emerging field of flexible electronics, which is primarily motivated by the desire to incorporate electronics into flexible substrates such as textiles, displays, and bandages [29]. The ability to reversibly deform antennas may also enable new capabilities (e.g., rolling and unrolling for remote deployment, enhanced durability). Relative to conventional copper antennas, fluidic antennas have several advantages [30]. Furthermore, it has been shown that ultrathin layers of metal can display superconductivity, but any limits on the size of superconducting systems remain a mystery.

On the other hand, (BETS) 2GaCl4, where BETS is bis (ethylenedithio) tetraselenafulvalene, is an organic superconductor, and in bulk it displays a superconducting gap that increases exponentially with the length of the molecular chain [31].

Graphene-solution-gated FET (G-SGFET) fabricated on copper foil offers outstanding electronic performance, is chemically stable and biologically inert, and can readily be processed on flexible substrates. Not only were the “action potentials” of individual cells detectable above the intrinsic electrical noise of the transistors, but these cellular signals could be recorded with high spatial and temporal resolution.

The analysis of the recorded cell signals and the electronic noise of the transistors confirm that graphene transistors surpass state-of-the-art devices for bioelectronic applications [32].

An organic FET (OFET) is characterized by textile process fully compatible size and geometry. This transistor has shown very interesting performances, with typical values of the electronic parameters very similar to those of planar devices. This result is very promising in view of innovative applications in the field of smart textiles [33]. Also FETs with single- and doublewire channels (NWFET) were fabricated to give some indication of the potential application of the molecular wires [22]. Finally, inkjet-printed FETs using carboxyl-functionalized nanotubes as source, drain, and gate electrodes, poly (ethylene glycol) (PEG-) functionalized nanotubes as the channel, and PEG as the gate dielectric were also tested and characterized. Considerable nonlinear transport in conjunction with a high channel current on/off

3

M+

Delivery M+

M+ D

M− G M−

CNT

Vout/in M−

S Diagnostic

Figure 1: Diagnostics of the biomedium with the necessary drugs delivering.

ratio of 70 was observed with PEG-functionalized nanotubes.

The positive temperature coefficient of channel resistance shows the nonmetallic behavior of the inkjet-printed films [34].

Finally, FETs with single- and doublewire channels were fabricated to give some indication of the potential application of the molecular wires. Substantial progress has been made in defining the performance limits and exploring applications based on NWFETs [22]. A five-channel FET structure is composed of two double-gate transistors and a bottom single-gate transistor on a silicon-on-insulator. 3D transistor structures such as multiple-gate FETs have been proposed and extensively studied as a promising solution to overcome the scaling limitations of planar bulk devices. They offer excellent multigate control of the channels and higher current drive [35]. In high-performance n-channel OFETs, charge carrier injection at the interface between the organic film and source/drain electrodes plays a crucial role [36].

3. An SuFETTr-Based Devices

Magnetic

Interface

The advent of semiconductor devices with nanoscale dimensions creates the potential to integrate nanoelectronics and optoelectronic devices with a great variety of biological systems. In such a case, it is possible to substitute the microcomputer in an object-oriented problem solution scheme by the natural processing organ-brain or spinal cord.

As a result, the software component will be eliminated and the most general characterization of the measurement problem in one-coordinate-dimensional measurements could be acquired naturally, according to the feedback reaction on the input exposure. Moreover, the organs of the senses of living beings could be regarded in the same way as the natural

4

ISRN Nanotechnology

Myelin

Channel’s ibio Vout/in

NI

Ionic currents H P

Gate

SuFET

(a)

Axons

Figure 2: Transducing of the nerve impulses and introducing of the relevant artificial signals [15].

(b)

(c)

B2a

B2b

B1a

B1b

(d)

(e)

B0a

B0b

Figure 3: PC for “two-dimensional” gradiometer that detects both axial-second-order gradient and planar-first-order gradient of MF [37]. Copyright 2007 The Japan Society of Applied Physics.

biosensors of the relevant physical and chemical quantities [19, 39].

The proposal to measure the biosignal values of different origins with advanced nanosensors of EM quantities is justified when allowing for superconducting abilities of the devices. They are composed in full-scale arrays. The said arrays can be both implantable into ionic channels of an organism and sheathed on the sources of the EM emanation.

Nanowired head sensors function both in passive mode for picking up the biosignals and with additional excitation of a defined biomedium through the same head (in reverse) [40– 42].

3.1. The Arrangements of a NanoFET-Based Delivery and Transducing. The advances in nanotechnology are opening

Figure 4: Comparison of the discrete geometry of three selfassembly models. (a) Unfolding an HP chain. (b)–(d) Several representations of unfolding a cube [38]. Copyright 2011 National Academy of Sciences, USA.

the way to achieving direct electrical contact of nanoelectronic structures with electrically and electrochemically active subcellular structures, including ion channels, receptors, and transmembrane proteins. The method of combining the bioelectric nature of the nerve impulses NI and synaptic currents between neighboring neurons with body-temperature PC and zero-resistance-CNT-based input of the SuFET device in order to obtain most advantageous biosensor/transducer was recently advanced [43]. On the other hand, neuroelectronic systems for two-way interfacing of the neuronal and the electronic components by capacitive contacts and by FETs with an open gate were developed.

A nanoSuFET with a high-temperature superconducting channel is introduced into the nerve fibre or brain tissue for transducing their signals in both directions.

Such a sensor/actuator is suitable for picking up BS—NI and electrically active (ionized) molecules—and transforming it into recognizable information in the form of electric

6

ISRN Nanotechnology Table 1: Dependence of the received BS parameters on the mode of SuFETTr’s functioning.

Mode

Medium

Serial External

NI Molecules DNA

!

!

ibio = 1cont. or sens. imp.

BSs → bio and chem. molec.

propagation of BS along DNA’s spirals

Parallel Implantable External ibio = ibio ( f1 ) + ibio ( f2 ) + dibio /dt, dibio /dx · · · + ibio ( fN ) " variation of BSs → BSs = 1 type of molec. concentr. of molec. decoding the BSs of space and length dynamic nucleoted recognition on both spirals

Implantable

"

"

ibio = 1 network or 1 fibre

BSs =

"

bio and chem. molec.

4 nucleoteds 4 outputs

Table 2: Measuring effects (values) and the relative nanotransducers (for interfacing).

single (passive) solid-state device EM transistor/memristor (EMTM) has been advanced [48] An attempt to lay down the foundations of biosensing by natural sensors and in addition to them by the artificial transducers of physical quantities, also with their expansion into space arrays and external/implantable functioning in relation to the nervous system, is performed. Because the sensing organs are exponentially better than any of analogous artificial ones, the advances in nanotechnology are opening the way to achieving direct electrical contact of nanoelectronic structures with electrically and electrochemically active neurocellular structures. The transmission of the sensors’ signals to a processing unit has been maintaining by an EM transistor/memristor (externally) and superconducting transducer of ionic currents (implantable). The arrays of the advanced sensors give us information about the space and direction dynamics of the signals’ spreading.

Recent developments in bioengineering, nanotechnology, and soft computing make it possible to create a new generation of intelligent sensing. There are developing opportunities for combining natural and artificial sensing abilities in the synthesized system. Backed up by the rapid strides of nanotechnology, nanosensor research is making a two-directional progress, firstly in evolving new sensors employing mesoscopic phenomena, and secondly in the performance enhancement of existing sensors. Nanosensors are nanotechnology-enabled sensors characterized by one of the following attributes: either the size of the sensor or its sensitivity is in the nanoscale, or the spatial interaction distance between the sensor and the object is in nanometers.

These nanosensors have been broadly classified into physical and chemical categories, with the biosensors placed on borderlines of biological signals with the remaining classes [49].

Multiprocessor data fusion is in effect intrinsically performed by animals and human beings to achieve a more

NW element PC(s) NIext EMTM induction transducer volume flowmeter

Superconducting membrane NIimpl acoustical EMTM noise absorb. universal flowmeter

A functional pattern of SuFETTr Informational flow Biological

EM field

Technical

el. current Electronic

Ionic el. voltage

Actuator

Ionic currents FerroEM Magnetic induction Magnetodynam.

SuFET channel NIimpl EMTM NIcontr gaseous flowmeter

Sensor

Physical value

Empirical data Biological

Technical Informational flow

Figure 7

accurate assessment of the processing environment. The aim of signal processing by the combined artificial-living being multiprocessor system is to acquire complete information, such as a decision or the measurement of quantity, using a selected set of input data streaming to a multiprocessor system-digital data are coming to artificial processor and the rest of information consumes by a neural system of living being (Figure 5). Thereby, a big amount of available information is managed using sophisticated data processing for the achievement of a high level of precision and reliability.

4. Results Application variety of the novel superconducting, organic, and CNTFETs allows us to design transducers of BS (nerve, biochemical, etc.) that transduce them into different quantities, including electric voltage, density of chemical and biomolecules. On the other hand, the said BS can

ISRN Nanotechnology

7 Table 3: Geometrical form of the distributed in space and time arrays.

Dimension

Value Array differential differential gradiometrical gradiometrical module gradiometrical differential module

Scalar module gradiometrical differential module gradiometrical module

point line curve plane

Vector triaxial differential triaxial differential triaxial gradiometrical triaxial

Tensor triaxial vector differential triaxial vector differential triaxial vector gradiometrical triaxial vector

Table 4: Dependence of the received structure parameters on the mode of functioning- passive (Figure 1) or active (Figure 2).

Device

Object

Passive modulus !!

I1 = s f (x, y, z)ds !!

V1 = s f (x, y)dxd y

surface volume structure level

Active modulus !!

I2 = s f (x, y, z)dxd y !!!

V2 = V f (x, y, z)dv investigation of the inside structure of the organs and tissues

drug delivery to sheath (envelopes) of organs

Passive gradient ∆I1 = I1! − I1!! ∆V1 = V1! − V1!!

Active gradient ∆I2 = I2! − I2!! ∆V2 = V2! − V2!!

comparing delivery to the differential investigation the organ’s or tissue’s areas twin (pair) organs or tissues

comparing delivery to the differential investigation the object (body) drug delivery to homogeneous investigation of inhomogeneous homogeneous organ’s or inhomogeneous twin (pair) level organs or tissues organs or tissues tissue’s areas organs or tissues

Two-way current transducers (TCTs)

EM head coil

MEG

Acoustical head coil

Neurointerface

Sensor

Flowmeter

External

EM (optical) transistor

Pickup coil CNT magnetometer (bio)physical/chemical

Implantable

Actuator

Conductor µ-ammeter

Figure 8

be controlled by the applied electrical signals or bio and chemical mediums.

The described SuFETTrs designed on the basis of organic and nano-SuFETs are suitable for describing the wide range of BS dynamical parameters (see Table 1). Following the columns of the table, it should be noticable that serial connection of the external PCs allows us to gain some integrated signal, that is, the whole sensing or control NI, which spreads along the number of axons of the nerve fibre: the amount of ions passing through the PCs and the generalized BS passing through one or both spirals of DNA. When SuFET channel(s) are implanted into the tissue or process, we can acquire more precise data about the frequency distribution of NI, volume distribution of ionized molecules and detecting activity of individual nucleotides.

Exploitation of the parallel input to SuFETTr allows determination of space and time dynamics of BS in the nerve fibre and DNA spiral(s) and also the amplification of output signal Uout by multiplying the concentration of molecules according to a number of input BS. After the implantation of parallel SuFET(s), the averaging or summation of this dynamic among the whole neural network, nerve fibre, or DNA spiral(s) is possible.

A number of both active and passive electronic elements are used with PCs. On the other hand, any particular element is susceptible by the effect of some specific physical quantity.

The relevant interfacing devices, which are acquired on the said basis, are shown in Table 2. As a result, a wide range of the biosensors allow both measuring the variety of magnetic signals and interface the EM signals with further stages of electronic systems.

The designed sensors are arranged in a space and time arrays for investigation of the biostructures of the different level of precision. This correspondence is established by composing the head sensors from Table 2 into the various gradiometry schemes from a simple planar to the 2d vector enclosing in Table 3. In Table 3, the geometrical dimensions from a point to volume ranges are transformed to the mathematical terms.

The described interfaces designed on the basis of SuFETTr are suitable for investigating both the structure of organic objects and their comparing analysis (see Table 4).

Following the strings of the table, it should be noticeable, that investigations of biological surfaces are performing according to the surface integrals for a passive and active signals’ moduluses, respectively. The surface gradients are acquired by finding the difference between the respective values of I1 or I2 . The same is applying to the investigations of biological volumes V1 and V2 as the double and triple

8 integrals respectively. The next two strings are explaining the bounds on the possible spreading of the said method.

The aggregated interface qualities, which are given in the tables, have been shown in the graph (Figure 6). Upon its analysis, it becomes clear that the area which is bounded by the dashed lines presents the MIs. At the same time, there are some uncertain areas (marked on the figure) that are inaccessible to the designed transducing elements.

Furthermore, the graph’s square is open to the right for perspective media of MIs.

5. Conclusions The reviewed variety of FETs shows the varying extent of readiness for them to be exploited in SuFETTr of electrical current signals (see Figure 7). The most appropriate for such an application are the ordinary solid-state SuFET modifications and novel CNT-based SuFETs. The organic SuFETs are not amply developed, but this work is being carried out in a number of directions. At the same time, the PCs, which are necessary for the external sensor with respect to the transducing medium (nerve fibre, flow of ions and DNA spiral), and corresponding low-ohmic wire traces for connecting PCs to the FET’s channel are sufficiently developed, even at nanodimensions.

The preliminary calculations confirm the possibility of broadening the SuFETTr’s action from magnetic field to the biochemical medium of BSs. The main parameters of such BSs can be gained by applying the arrangement of the SuFETTr(s) to the whole measurement system. Two directions of SuFETTr function enable decoding of the BS by comparing the result of its action on some process or organ with an action on them of the simulated electrical or biochemical signal after their reverse transducing through the SuFETTr(s). Furthermore, this decoded signal will provide a basis for creating feedback and feedforward loops in the measuring system for more precise and complete influence on the biochemical process.

The advance in the instrumentation techniques and technology of materials allows introducing of more accurate methods of interfacing and transducers for their execution (see Figure 8). At this level of progress, the head sensors of paramount sensitivity and simplicity in picking up function with minimal changes of the physical variables. The recent breakthrough in superconducting- and nanotechnologies caused the creation of induction transducers, which have better informational capability in some diagnostical purposes.

These devices are based on the universal law of the EM induction on the one hand and different special effects of MF interaction with a medium on the other. Since the proposed variety of bio-nano-sensors are passive, they do not affect the functions of the organs and their interaction.

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