ISRN NanotechnologyVolume 2012 (2012), Article ID 102783, 9 pagesdoi:10.5402/2012/102783

Review Article

A CNTFET-Based Nanowired Induction Two-Way Transducers

Rostyslav Sklyar

Verchratskogo st. 15-1, Lviv 79010, Ukraine

Received 15 December 2011; Accepted 28 February 2012

Academic Editors: C. A. Charitidis and J. Sha

Copyright © 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.

Abstract.

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 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. 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, implantable-into-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 base-pair 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, 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 carbon- nanotubes- (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 (DG-SiNW), 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 nanomaterials, have attracted considerable attention because of their potential applications, such as parts for nano- or 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 ) [26] and coplanar SuFET (high ) [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 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 Magnetic Interface Devices

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 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 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 voltage, or a concentration of organic or chemical substances (Figure 1). Moreover, this process can be executed in reverse. Substances and/or voltages influence BS, thereby controlling or creating the said media (Figure 2).

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

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

As a result, we have achieved SuFETTr that is suitable for ascertaining the variety of values. Two directions of SuFETTr function enable decoding of the NI by comparing the result of its reaction 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) [44].

3.2. Arrangement of PSs in Arrays

An MF sensing array consists of primary sensors and, optionally, reference sensors. Primary sensors use flux transformers located in a close proximity to the scalp or chest surface, where they couple to the brain’s or heart’s MFs, respectively [7, 45]. The reference sensors are used to subtract the environmental noise from the primary sensor outputs. The flux transformer design dictates its relative sensitivity to near and distant sources. Thus, the primary flux transformers can, in addition to detecting the brain signals, also provide various degrees of the environmental noise rejection. Flux transformers (magnetometers) have the highest sensitivity to both near- and far-field sources. Thus, they do not reduce the environmental noise (and must rely solely on the references or other techniques for the noise cancellation) [16].

Wire-wound gradiometers are the most conventional and are commercially available for EM systems. The PCs of wire-wound gradiometers are wound in opposition and balanced so that a uniform field links the zero net flux [37]. Conventional gradiometers, such as wire-wound, thin-film, or electronic gradiometers, are axial or planar, that is, ‘‘one dimensional’’ that detect the gradient of a MF in one direction. These one-dimensional gradiometers effectively reduce the ambient MF as their order increases. However, they also reduce the biomagnetic signal. A ‘‘two-dimensional’’ gradiometer detects the gradient of an MF in two orthogonal directions to achieve high SNR. It focuses on a two-dimensional gradiometer that detects both the axial-second-order and planar-first-order gradients of an MF. Figure 3 shows a PC for the two-dimensional gradiometer.

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.

The discrete configuration space is a graph. Each node in the graph corresponds to an intermediate, and its neighbors are intermediates to which it can be folded or unfolded [38]. A common feature shared by folding of hydrophobic-polar chains on a lattice and self-folding a net through vertex connections is that in both cases the process of folding is driven by the formation of secondary links between topological neighbors (Figure 4). The best 2D arrangements, called planar nets, to create self-folding polyhedra with dimensions of a few hundred microns are determined, and optimal configurations for creating 3D geometric shapes have been found.

(a)

(b)

(c)

(d)

(e)

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

The importance of being able to address nanoscale elements in arrays goes beyond the area of nanocomputing and will be critical to the realization of other integrated nanosystems such as chemical/biological sensors. A regular crossed-NW FET array that consists of n-input and m-output NWs, in which outputs are the active channels of FETs and the inputs function as gate electrodes that turn these output lines on and off [46, 47].

3.3. Multisensor Data Fusion from Arrays

A further step should be synthesis of the said two methods in order to develop the external (nonimplantable) MCG&MEG signals-to-processor connection. The EM sensors are surface PCs, which are used in regular configuration where PCs with a small distance between each other are distributed under the heart or brain surface to pick up the local signals within the place of interest. The problem of sensing the EM signal for amplification/switching/memory with a speed of light in a 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 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.

Figure 5: Interaction of the natural and artificial processing bodies trough a SuFETTr-based interface.

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 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.

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

Medium
Mode

Serial
Parallel

External
Implantable
External
Implantable

NI
cont. or sens. imp.

network or fibre

Molecules

.
.
.

DNA
propagation of BS along DNA’s spirals
decoding the BSs of nucleoted recognition
space and length dynamic on both spirals
4 nucleoteds 4 outputs

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 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.

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

Physical value
NW element

SuFET channel
PC(s)
Superconducting membrane

Ionic currents

FerroEM
EMTM
EMTM
acoustical EMTM

Magnetic induction

induction transducer
noise absorb.

Magnetodynam.
gaseous flowmeter
volume flowmeter
universal flowmeter

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.

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

Dimension
Value

Scalar
Array
Vector
Tensor

Point
module
differential
triaxial
triaxial vector

Line
gradiometrical
differential gradiometrical
differential triaxial
differential triaxial vector

Curve
differential module
gradiometrical module
differential triaxial
differential triaxial vector

Plane
gradiometrical module
gradiometrical differential module
gradiometrical triaxial
gradiometrical triaxial vector

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 or . The same is applying to the investigations of biological volumes and as the double and triple integrals respectively. The next two strings are explaining the bounds on the possible spreading of the said method.

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

Object
Device

Passive modulus
Active modulus
Passive gradient
Active gradient

Surface

Volume

Structure level
drug delivery to sheath (envelopes) of organs
investigation of the inside structure of the organs and tissues
comparing delivery to the organ’s or tissue’s areas
differential investigation the twin (pair) organs or tissues

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

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.

Figure 6: Interfacing ability (power) of the specific input elements. It depends on two groups of space characteristics (form and direction) for the available transducing media.

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.

Figure 7

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.

Figure 8

References

F. Lucarelli, G. Marrazza, A. P. F. Turner, and M. Mascini, “Carbon and gold electrodes as electrochemical transducers for DNA hybridisation sensors,” Biosensors and Bioelectronics, vol. 19, no. 6, pp. 515–530, 2004.

A. D. Wilson and M. Baietto, “Advances in electronic-nose technologies developed for biomedical applications,” Sensors, vol. 11, no. 1, pp. 1105–1176, 2011.

Y. Lin, “A natural contact sensor paradigm for nonintrusive and real-time sensing of biosignals in human-machine interactions,” IEEE Sensors Journal, vol. 11, no. 3, pp. 522–529, 2011.

K. T. Ng, T. E. Batchman, S. Pavlica, and D. L. Veasey, “Noise and sensitivity analysis for miniature E-field probes,” IEEE Transactions on Instrumentation and Measurement, vol. 38, no. 1, pp. 27–31, 1989.

H. Itozaki, S. Tanaka, T. Nagaishi, and H. Kado, “Multi-channel high SQUID,” IEICE Transactions on Electronics, vol. E77-C, no. 8, pp. 1185–1190, 1994.

O. V. Lounasma, J. Knuutila, and R. Salmelin, “Squid technology and brain research,” Physica B, vol. 197, no. 1-4, pp. 54–63, 1994.

R. Sklyar, “An EM transistor based brain-processor interface,” in Nanotechnology 2009: Life Sciences, Medicine, Diagnostics, Bio Materials and Composites, vol. 2, chapter 3: Nano Medicine, pp. 131–134, CRC Press, Houston, Tex, USA, 2009, http://www.nsti.org/procs/Nanotech2009v2/3/T82.602.

R. Sklyar, “Induction magnetic field biosensors: from the macro to nano dimensions,” in Proceedings of the 1st Bio-Sensing Technology Conference, Bristol, UK, November 2009, paper P2.3.13 (2 pages) of the abstract book.

A. Kandori, D. Suzuki, K. Yokosawa et al., “A superconducting quantum interference device magnetometer with a room-temperature pickup coil for measuring impedance magnetocardiograms,” Japanese Journal of Applied Physics I, vol. 41, no. 2 A, pp. 596–599, 2002.

R. Sklyar, “Superconducting induction magnetometer,” IEEE Sensors Journal, vol. 6, no. 2, pp. 357–364, 2006.

P. Fromherz, “Electrical interfacing of nerve cells and semiconductor chips,” ChemPhysChem, vol. 3, pp. 276–284, 2002.

Y. Cui, Q. Wei, H. Park, and C. M. Lieber, “Nanowire nanosensors for highly sensitive and selective detection of biological and chemical species,” Science, vol. 293, no. 5533, pp. 1289–1292, 2001.

R. Sklyar, “From nanosensors to the artificial nerves and neurons,” in Proceedings of the Nanotechnology in Industrial Applications (EuroNanoForum '07), pp. 166–168, CCD, Düsseldorf, Germany, June 2007.

R. Sklyar, “Superconducting organic and CNT FETs as a Biochemical Transducer,” in Proceedings of the 14th International Symposium on Measurement and Control in Robotics (ISMCR '04), IEEE, Houston, Tex, USA, September 2004.

R. Sklyar, “A SuFET based either implantable or non-invasive (Bio)transducer of nerve impulses,” in Measurement and Control in Robotics, M. A. Armada, P. Gonzales de Santos, and S. Tachi, Eds., pp. 121–126, Producción Gráfica Multimedia, Madrid, Spain, 2003.

J. Vrba and S. E. Robinson, “SQUID sensor array configurations for magnetoencephalography applications,” Superconductor Science and Technology, vol. 15, no. 9, pp. R51–R89, 2002.

V. Zalyubovskiy, A. Erzin, S. Astrakov, and H. Choo, “Energy-efficient area coverage by sensors with two adjustable ranges,” Sensors, vol. 9, pp. 2446–2460, 2009.

X. Chen and O. Bai, “Towards multi-dimensional robotic control via noninvasive brain-computer interface,” in Proceedings of the ICME International Conference on Complex Medical Engineering (CME '09), Tempe, Ariz, USA, April 2009.

R. Sklyar, “Sensors with a bioelectronic connection,” IEEE Sensors Journal, vol. 7, no. 5, pp. 835–841, 2007.

J. Shui and J. C. M. Li, “Platinum nanowires produced by electrospinning,” Nano Letters, vol. 9, no. 4, pp. 1307–1314, 2009.

N. Misra, J. A. Martinez, S. C. J. Huang et al., “Bioelectronic silicon nanowire devices using functional membrane proteins,” Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 33, pp. 13780–13784, 2009.

J. Hobden, “Self assembled molecular nanowires: electronic properties,” Nano Today, vol. 3, no. 5-6, p. 11, 2008.

Y. Nakayama, “Plasticity of carbon nanotubes: aiming at their use in nanosized devices,” Japanese Journal of Applied Physics I, vol. 46, no. 8, pp. 5005–5014, 2007.

R. Kanada, L. Pan, S. Akita, N. Okazaki, K. Hirahara, and Y. Nakayama, “Synthesis of multiwalled carbon nanocoils using codeposited thin film of Fe-Sn as catalyst,” Japanese Journal of Applied Physics, vol. 47, no. 4, pp. 1949–1951, 2008.

D. C. Ng, T. Nakagawa, T. Mizuno et al., “Integrated in vivo neural imaging and interface CMOS devices: design, packaging, and implementation,” IEEE Sensors Journal, vol. 8, no. 1, pp. 121–130, 2008.

J. F. Jiang, Q. Y. Cai, H. M. Jiang, Y. S. Tang, and Z. L. Zhong, “High-performance complementary metal-oxide-superconductor field effect transistor (CMOSuFET) current-mode operational amplifier,” Superconductor Science and Technology, vol. 9, no. 4, pp. A66–A70, 1996.

S. Suzuki, H. Tobisaka, and S. Oda, “Electric properties of coplanar high- superconducting field-effect devices,” Japanese Journal of Applied Physics I, vol. 37, no. 2, pp. 492–495, 1998.

R. Sklyar, “The microfluidic sensors of liquids, gases,and tissues based on the CNT or organic FETs,” Journal of Automation, Mobile Robotics and Intelligent Systems, vol. 1, no. 2, pp. 20–34, 2007, http://www.jamris.org/02_2007/20.jpg

R. Sklyar, “Application of the flexible pickup coils in connection with OFETs for distribution e-textile sensors in an array,” in Proceedings of the Large-area, Organic & Printed Electronics Convention (LOPE-C '10), pp. 227–232, 2010.

J. H. So, J. Thelen, A. Qusba, G. J. Hayes, G. Lazzi, and M. D. Dickey, “Reversibly deformable and mechanically tunable fluidic antennas,” Advanced Functional Materials, vol. 19, no. 22, pp. 3632–3637, 2009.

K. Clark, A. Hassanien, S. Khan, et al., “Superconductivity in just four pairs of (BETS)₂GaCl₄ molecules,” Nature Nanotechnology, vol. 5, pp. 261–265, 2010, http://www.nature.com/nnano/journal/v5/n4/abs/nnano.2010.41.html

L. H. Hess, M. Jansen, V. Maybeck, et al., “Graphene transistor arrays for recording action potentials from electrogenic cells,” Advanced Materials, vol. 23, no. 43, pp. 5045–5049, 2011.

M. Maccioni, E. Orgiu, P. Cosseddu, S. Locci, and A. Bonfiglio, “Towards the textile transistor: assembly and characterization of an organic field effect transistor with a cylindrical geometry,” Applied Physics Letters, vol. 89, no. 14, Article ID 143515, 2006.

E. Gracia-Espino, G. Sala, F. Pino et al., “Electrical transport and field-effect transistors using inkjet-printed SWCNT films having different functional side groups,” ACS Nano, vol. 4, no. 6, pp. 3318–3324, 2010, http://pubs.acs.org/doi/abs/10.1021/nn1000723

E. Bernard, T. Ernst, B. Guillaumot et al., “Multi-Channel Field-Effect Transistor (MCFET)—part I: electrical performance and current gain analysis,” IEEE Transactions on Electron Devices, vol. 56, no. 6, pp. 1243–1251, 2009.

X. Cai, J. Yu, J. Zhou, et al., “Mobility improvement in C60-based field-effect transistors using LiF/Ag source/drain electrodes,” Japanese Journal of Applied Physics, vol. 50, Article ID 124203, 2011.

Y. Seki and A. Kandori, “Two-dimensional gradiometer,” Japanese Journal of Applied Physics I, vol. 46, no. 6A, pp. 3397–3401, 2007.

S. Pandeya, M. Ewingb, A. Kunasc, et al., “Algorithmic design of self-folding polyhedra,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, no. 50, pp. 19885–19890, 2011.

R. Sklyar, “Machine perception through natural intelligence,” Positioning, vol. 2, pp. 65–77, 2011, http://www.scirp.org/journal/PaperInformation.aspx?paperID=5051#abstract

R. Sklyar, “A complex of the electromagnetic biosensors with a nanowired pickup,” J. of Sensors, vol. 2009, Article ID 516850, 20 pages, 2009, http://www.hindawi.com/journals/js/2009/516850/

R. Sklyar, “A SuFET based sensor for nano-microscope,” Journal of Automation, Mobile Robotics and Intelligent Systems (JAMRIS), no. 3, pp. 3–20, 2007, http://www.jamris.org/03_2007/03.jpg

R. Sklyar, “Pierced sensor for nano-microscope (NMSC),” in Nanotechnology 2009: Fabrication, Particles, Characterization, MEMS, Electronics and Photonics (Nanotech '09), vol. 1, chapter 7: Sensors and Systems, pp. 546–549, CRC Press, Houston, Tex, USA, May 2009, http://www.nsti.org/procs/Nanotech2009v1/7/T81.301.

R. Sklyar, “CNT and organic FETs based two-way transducing of the neurosignals,” in Nanotechnology 2008: Life Sciences, Medicine, and Bio Materials (Nanotech '08), vol. 2 of Nano Medicine & Neurology, chapter 6, pp. 475–478, Cambridge, Mass, USA, CRC Press, 2008, http://www.nsti.org/procs/Nanotech2008v2/6/M81.404.

R. Sklyar, “Direct bio (Living Being) sensors-to-processing unit interface,” in Proceedings of the 4th Security Research Conference: Fraunhofer Alliance for Defense and Security Research VVS: Future Security, P. Elsner, Ed., pp. 290–309, Fraunhofer IRB, Karlsruhe, Germany, September 2009.

R. Sklyar, “Direct processing of the MCG and MEG signals,” in Proceedings of the 6th International Conference on Biomedical Applications of Nanotechnology (NanoMed '09), p. 137, Charite, Germany, March 2009.

Z. Zhong, D. Wang, Y. Cui, M. W. Bockrath, and C. H. Lieber, “Nanowire crossbar arrays as address decoders for integrated nanosystems,” Science, vol. 302, no. 5649, pp. 1377–1379, 2003.

R. Sklyar, “Two-way interface for directing the biological signals,” European Cells and Materials, vol. 14, supplement 3, 37 pages, 2007, http://www.ecmjournal.org/journal/supplements/vol014supp03/pdf/v014supp03a037.pdf

R. Sklyar, “The method of instant amplification of the MCG&MEG signals,” in Nanotechnology 2010: Bio Sensors, Instruments, Medical, Environment and Energy (Nanotech '10), vol. 3, chapter 7 of Nano Medical Sciences, pp. 467–470, CRC Press, 2010, http://www.nsti.org/procs/Nanotech2010v3/7/T40.615.

V. K. Khanna, “Frontiers of nanosensor technology,” Sensors & Transducers Journal, vol. 103, no. 4, pp. 1–16, 2009.