Charge carrier distribution changes in solid substrates induced by the presence of biomolecules have the potential as sensoric principle. For a high surface-to-bulk ratio as in the case of nanostructures, this effect can be used for highly sensitive bioanalytics. Plasmonic nanosensors represent one possible implementation: The resonance wavelength of the conductive electron oscillation under light irradiation is changed upon molecular binding at the structure surface. This change can be detected by spectroscopic means, even on a single nanoparticle level using microspectroscopy. Other examples are nanowires in electrodes gaps, either by metal nanoparticles arranged in a chain-like geometry or by rod-like semiconductor nanowires directly bridging the gap. Molecules binding at the surface will lead to changes in the electrical conductivity which can be easily converted into an electrical readout. The various geometries will be discussed and their sensoric potential for an electrical detection demonstrated.

DNA microarrays can provide bacterial identification, which is crucial for targeted therapy. However they lack rapidness, because of multiple analysis steps. Therefore a fast one-step method for synthesising a hybridisation-ready reagent out of initial bacterial DNA is required. This work presents the combination and acceleration of PCR and fluorescent labelling within a disposable microfluidic chip, fabricated by injection moulding. The utilised geometry consists of a spiral meander with 40 turns, representing a cyclic-flow PCR system. The used reaction chemistry includes Cy3-conjugated primers and a high-yield polymerase leading to a one-step process accelerated by cyclic-flow PCR. Three different bacterial samples (Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa) were processed and the bacterial DNA was successfully amplified and labelled with detection limits down to 10² cells per reaction. The specificity of species identification was comparable to the approach of separate PCR and labelling. Furthermore the overall processing time was decreased from 6 hours to 1.5 hours. We showed that a disposable polycarbonate chip, fabricated by injection moulding is suitable for the significant acceleration of DNA microarray assays. The reaction output lead to high-sensitivity bacterial identification in a short time, which is crucial for an early and targeted therapy against infectious diseases.

Tactile sensors have increasing presence in different applications, especially in assistive robotics or medicine and rehabilitation. They are basically an array of force sensors (tactels) and they are intended to emulate the human skin. Large sensors must be implemented with large area oriented technologies like screen printing. The authors have proposed and made some piezoresistive sensors with this technology. They consist of a few layers of conductive tracks to implement the electrodes and elastomers to insulate them, on a polymer substrate. Another conductive sheet is placed atop the obtained structure. Pressure distribution in the interface between this conductive sheet and the electrodes has a direct impact on the sensor performance. The mechanical behavior of the layered topology with conductive tracks, elastomers and polymers must be studied. For instance, the authors have observed experimentally the existence of pressure thresholds in the response of their sensors. Finite element simulations with COMSOL explain the reason for such thresholds as well as the dependence of the pressure distribution profile on the properties of the materials and the geometry of the tactel. This paper presents results from these simulations and the main conclusions that can be obtained from them related to the design of the sensor.

For the HapCath system, which provides haptic feedback of the forces acting on a guide wire's tip during vascular catheterization, very small piezoresistive force sensors of 200•200•640μm³ have been developed. This paper focuses on the characterization of the measurement performance and on possible new applications. Besides the determination of the dynamic measurement performance, special focus is put onto the results of the 3- component force vector calibration. This article addresses special advantageous characteristics of the sensor, but also the limits of applicability will be addressed. As for the special characteristics of the sensor, the second part of the article demonstrates new applications which can be opened up with the novel force sensor, like automatic navigation of medical or biological instruments without impacting surrounding tissue, surface roughness evaluation in biomedical systems, needle insertion with tactile or higher level feedback, or even building tactile hairs for artificial organisms.

Gaussian filtering is a basic tool for image processing. Noise reduction, scale-space generation or edge detection are examples of tasks where different Gaussian filters can be successfully utilized. However, their implementation in a conventional digital processor by applying a convolution kernel throughout the image is quite inefficient. Not only the value of every single pixel is taken into consideration sucessively, but also contributions from their neighbors need to be taken into account. Processing of the frame is serialized and memory access is intensive and recurrent. The result is a low operation speed or, alternatively, a high power consumption. This inefficiency is specially remarkable for filters with large variance, as the kernel size increases significantly. In this paper, a different approach to achieve Gaussian filtering is proposed. It is oriented to applications with very low power budgets. The key point is a reconfigurable focal-plane binning. Pixels are grouped according to the targeted resolution by means of a division grid. Then, two consecutive shifts of this grid in opposite directions carry out the spread of information to the neighborhood of each pixel in parallel. The outcome is equivalent to the application of a 3×3 binomial filter kernel, which in turns is a good approximation of a Gaussian filter, on the original image. The variance of the closest Gaussian filter is around 0.5. By repeating the operation, Gaussian filters with larger variances can be achieved. A rough estimation of the necessary energy for each repetition until reaching the desired filter is below 20nJ for a QCIF-size array. Finally, experimental results of a QCIF proofof- concept focal-plane array manufactured in 0.35μm CMOS technology are presented. A maximum RMSE of only 1.2% is obtained by the on-chip Gaussian filtering with respect to the corresponding equivalent ideal filter implemented off-chip.

This paper presents a Dynamic Range improvement technique which is specially well-suited to be implemented in Focal Plane Processors (FPP) due to its very limited computing requirements since only local memories, little digital control and a comparator are required at the pixel level. The presented algorithm employs measurements during exposure time to create a 4-bit non-linear image whose histogram determines the shape of the tone-mapping curve which is applied to create the final image. Simulations results over a highly bimodal 120dB image are presented showing that both the highly and poorly illuminated parts of the image keep a sufficient level of details.

Single-photon avalanche diodes are compatible with standard CMOS. It means that photo-multipliers for scintillation detectors in nuclear medicine (i. e. PET, SPECT) can be built in inexpensive technologies. These silicon photo-multipliers consist in arrays of, usually passively-quenched, SPADs whose output current is sensed by some analog readout circuitry. In addition to the implementation of photosensors that are sensitive to singlephoton events, analog, digital and mixed-signal processing circuitry can be included in the same CMOS chip. For instance, the SPAD can be employed as an event detector, and with the help of some in-pixel circuitry, a digitized photo-multiplier can be built in which every single-photon detection event is summed up by a counter. Moreover, this concurrent processing circuitry can be employed to realize low level image processing tasks. They can be efficiently implemented by this architecture given their intrinsic parallelism. Our proposal is to operate onto the light-induced signal at the focal plane in order to obtain a more elaborated record of the detection. For instance, by providing some characterization of the light spot. Information about the depth-of-interaction, in scintillation detectors, can be derived from the position and shape of the scintillation light distribution. This will ultimately have an impact on the spatial resolution that can be achieved. We are presenting the design in CMOS of an array of detector cells. Each cell contains a SPAD, an MOS-based passive quenching circuit and drivers for the column and row detection lines.

Visual learning is an important aspect of fly life. Flies are able to extract visual cues from objects, like colors, vertical and horizontal distributedness, and others, that can be used for learning to associate a meaning to specific features (i.e. a reward or a punishment). Interesting biological experiments show trained stationary flying flies avoiding flying towards specific visual objects, appearing on the surrounding environment. Wild-type flies effectively learn to avoid those objects but this is not the case for the learning mutant rutabaga defective in the cyclic AMP dependent pathway for plasticity. A bio-inspired architecture has been proposed to model the fly behavior and experiments on roving robots were performed. Statistical comparisons have been considered and mutant-like effect on the model has been also investigated.

Behavioral experiments on fruit flies had shown that they are attracted by near objects and they prefer front-to-back motion. In this paper a visual orientation model is implemented on the Eye-Ris vision system and tested using a roving platform. Robotic experiments are used to collect statistical data regarding the system behaviour: followed trajectories, dwelling time, distribution of gaze direction and others strictly resembling the biological experimental setup on the flies. The statistical analysis has been performed in different scenarios where the robot faces with different object distribution in the arena. The acquired data has been used to validate the proposed model making a comparison with the fruit fly experiments.

The purpose of the current paper is to describe how different visual routines can be developed and embedded in the AnaFocus' Eye-RIS Vision System on Chip (VSoC) to close the perception to action loop within the roving robots developed under the framework of SPARK II European project. The Eye-RIS Vision System on Chip employs a bio-inspired architecture where image acquisition and processing are truly intermingled and the processing itself is carried out in two steps. At the first step, processing is fully parallel owing to the concourse of dedicated circuit structures which are integrated close to the sensors. At the second step, processing is realized on digitally-coded information data by means of digital processors. All these capabilities make the Eye-RIS VSoC very suitable for the integration within small robots in general, and within the robots developed by the SPARK II project in particular. These systems provide with image-processing capabilities and speed comparable to high-end conventional vision systems without the need for high-density image memory and intensive digital processing. As far as perception is concerned, current perceptual schemes are often based on information derived from visual routines. Since real world images are quite complex to be processed for perceptual needs with traditional approaches, more computationally feasible algorithms are required to extract the desired features from the scene in real time, to efficiently proceed with the consequent action. In this paper the development of such algorithms and their implementation taking full advantage of the sensing-processing capabilities of the Eye-RIS VSoC are described.

In order to make blood sample tests an artificial skin similar to that of the baby's heel is modeled and realized. The most superficial bloodstream and the two main layers of the skin -epidermis and dermis- have to be recreated. Studies and capillaroscopies of the baby's heel give characteristics of these layers and the bloodstream. The skin is viscohyperelastic, but the choice of materials that will be used is based on the Young's modulus. The epidermis layer is based on a stronger less adhesive silicon rubber Elastosil. The dermis layer is composed of a mixture based on a very soft sticky silicon rubber Silgel and Sylgard. The mixture of Silgel with 5% Sylgard has an elastic modulus of 48 kPa which is similar to that of the dermis. The artificial skin is an assembly of several layers including a layer of Sylgard that is structured by a mold representing the capillary network and adapted to manufacturing processes in a clean room. Each layer is deposited by spin coating and is combined with the other through adhesion. Mechanical tests such as tension are performed to verify the mechanical properties of the artificial skin.

Porous silicon (PSi) is by far a very useful technological platform for optical monitoring of chemical and biological substances and due to its peculiar physical and morphological properties it is worldwide used in sensing experiments. On the other hand, we have discovered a natural material, the micro-shells of marine diatoms, ubiquitous unicellular algae, which are made of hydrated amorphous silica, but, most of all, show geometrical structures made of complex patterns of pores which are surprisingly similar to those of porous silicon. Moreover, under laser irradiation, this material is photoluminescent and the photoluminescence is very sensitive to the surrounding atmosphere, which means that the material can act as a transducer. Starting from our experience on PSi devices, we explore the optical and photonic properties of marine diatoms micro-shells in a sort of inverse biomimicry.

The modified optical disc process has been investigated and demonstrated to enable fast prototyping in fabricating molds and replicating substrates with various microstructures including micro-chambers and micro-channels. A disc-like microfluidic device was created and the testing results showed good performance in bonding and packaging. The switching of the nozzle-like micro-valve was also validated to work well. Furthermore, the relevant procedures of liquid samples loading, separating and mixing were also accomplished through food experiments.

This work describes a software/hardware framework where cognitive architectures can be realized and applied to control different kinds of robotic platforms. The framework can be interfaced with a robot prototype mediating the sensory-motor loop. Moreover 2D and 3D kinematic or dynamic simulation environments can be used to evaluate the robotic system cognitive capabilities. Here, we address design choices and implementation issues related to the proposed robotic programming environment, taking attention to its modular structure, important characteristic for a flexible and powerful framework. The main advantage introduced by the proposed architecture consists in the rapid development of applications, that can be easily tested on different robotic platforms either real or simulated, because the differences are properly masked by the architecture. Simultaneously, to validate the functionality of the proposed system an "ad hoc" simulator is implemented.

Speech processing in the human brain is a very complex process far from being fully understood although much progress has been done recently. Neuromorphic Speech Processing is a new research orientation in bio-inspired systems approach to find solutions to automatic treatment of specific problems (recognition, synthesis, segmentation, diarization, etc) which can not be adequately solved using classical algorithms. In this paper a neuromorphic speech processing architecture is presented. The systematic bottom-up synthesis of layered structures reproduce the dynamic feature detection of speech related to plausible neural circuits which work as interpretation centres located in the Auditory Cortex. The elementary model is based on Hebbian neuron-like units. For the computation of the architecture a flexible framework is proposed in the environment of Matlab®/Simulink®/HDL, which allows building models in different description styles, complexity and implementation levels. It provides a flexible platform for experimenting on the influence of the number of neurons and interconnections, in the precision of the results and in performance evaluation. The experimentation with different architecture configurations may help both in better understanding how neural circuits may work in the brain as well as in how speech processing can benefit from this understanding.

Animals for surviving have developed cognitive abilities allowing them an abstract representation of the environment. This Internal Representation (IR) could contain a huge amount of information concerning the evolution and interactions of the elements in their surroundings. The complexity of this information should be enough to ensure the maximum fidelity in the representation of those aspects of the environment critical for the agent, but not so high to prevent the management of the IR in terms of neural processes, i.e. storing, retrieving, etc. One of the most subtle points is the inclusion of temporal information, necessary in IRs of dynamic environments. This temporal information basically introduces the environmental information for each moment, so the information required to generate the IR would eventually be increased dramatically. The inclusion of this temporal information in biological neural processes remains an open question. In this work we propose a new IR, the Compact Internal Representation (CIR), based on the compaction of spatiotemporal information into only space, leading to a stable structure (with no temporal dimension) suitable to be the base for complex cognitive processes, as memory or learning. The Compact Internal Representation is especially appropriate for be implemented in autonomous robots because it provides global strategies for the interaction with real environments (roving robots, manipulators, etc.). This paper presents the mathematical basis of CIR hardware implementation in the context of navigation in dynamic environments. The aim of such implementation is the obtaining of free-collision trajectories under the requirements of an optimal performance by means of a fast and accurate process.

Animals for surviving have developed cognitive abilities allowing them an abstract representation of the environment. This internal representation (IR) may contain a huge amount of information concerning the evolution and interactions of the animal and its surroundings. The temporal information is needed for IRs of dynamic environments and is one of the most subtle points in its implementation as the information needed to generate the IR may eventually increase dramatically. Some recent studies have proposed the compaction of the spatiotemporal information into only space, leading to a stable structure suitable to be the base for complex cognitive processes in what has been called Compact Internal Representation (CIR). The Compact Internal Representation is especially suited to be implemented in autonomous robots as it provides global strategies for the interaction with real environments. This paper describes an FPGA implementation of a Causal Neural Network based on a modified FitzHugh-Nagumo neuron to generate a Compact Internal Representation of dynamic environments for roving robots, developed under the framework of SPARK and SPARK II European project, to avoid dynamic and static obstacles.

Oscillatory networks are a special class of neural networks where each neuron exhibits time periodic behavior. They represent bio-inspired architectures which can be exploited to model biological processes such as the binding problem and selective attention. In most of situations, each neuron is assumed to have a stable limit cycle as the unique attractor. In this paper we investigate the dynamics of networks whose neurons are hard oscillators, namely they exhibit the coexistence of a stable limit cycle and a stable equilibrium point. We consider a constant external stimulus applied to each neuron, which influences the neuron's own natural frequency. We investigate the bifurcations in the neuron's dynamics induced by the input. We show that, due to the interaction between different kind of attractors, as well as between attractors and repellors, new interesting dynamics arises, in the form of synchronous oscillations of various amplitudes. We also show that neurons subject to different stimuli are able to synchronize if their couplings are strong enough.

Approximately 1% of the world's population suffer from epileptic seizures throughout their lives that mostly come without sign or warning. Thus, epilepsy is the most common chronical disorder of the neurological system. In the past decades, the problem of detecting a pre-seizure state in epilepsy using EEG signals has been addressed in many contributions by various authors over the past two decades. Up to now, the goal of identifying an impending epileptic seizure with sufficient specificity and reliability has not yet been achieved. Cellular Nonlinear Networks (CNN) are characterized by local couplings of dynamical systems of comparably low complexity. Thus, they are well suited for an implementation as highly parallel analogue processors. Programmable sensor-processor realizations of CNN combine high computational power comparable to tera ops of digital processors with low power consumption. An algorithm allowing an automated and reliable detection of epileptic seizure precursors would be a"huge step" towards the vision of an implantable seizure warning device that could provide information to patients and for a time/event specific treatment directly in the brain. Recent contributions have shown that modeling of brain electrical activity by solutions of Reaction-Diffusion-CNN as well as the application of a CNN predictor taking into account values of neighboring electrodes may contribute to the realization of a seizure warning device. In this paper, a CNN based predictor corresponding to a spatio-temporal filter is applied to multi channel EEG data in order to identify mutual couplings for different channels which lead to a enhanced prediction quality. Long term EEG recordings of different patients are considered. Results calculated for these recordings with inter-ictal phases as well as phases with seizures will be discussed in detail.

For processing of EEG signals, we propose a new architecture for the hardware emulation of discrete-time Cellular Nonlinear Networks (DT-CNN). Our results show the importance of a high computational accuracy in EEG signal prediction that cannot be achieved with existing analogue VLSI circuits. The refined architecture of the processing elements and its resource schedule, the cellular network structure with local couplings, the FPGA-based embedded system containing the DT-CNN, and the data flow in the entire system will be discussed in detail. The proposed DT-CNN design has been implemented and tested on an Xilinx FPGA development platform. The embedded co-processor with a multi-threading kernel is utilised for control and pre-processing tasks and data exchange to the host via Ethernet. The performance of the implemented DT-CNN has been determined for a popular example and compared to that of a conventional computer.

This paper presents a power efficient architecture for a neural spike recording channel. The channel offers a selfcalibration operation mode and can be used both for signal tracking (to raw digitize the acquired neural waveform) and feature extraction (to build a PWL approximation of the spikes in order to reduce data bandwidth on the RF-link). The neural threshold voltage is adaptively calculated during the spike detection period using basic digital operations. The neural input signal is amplified and filtered using a LNA, reconfigurable Band-Pass Filter, followed by a fully reconfigurable 8-bit ADC. The key element is the ADC architecture. It is a binary search data converter with a SCimplementation. Due to its architecture, it can be programmed to work either as a PGA, S&H or ADC. In order to allow power saving, inactive blocks are powered off depending on the selected operation mode, ADC sampling frequency is reconfigured and bias current is dynamically adapted during the conversion. Due to the ADC low input capacitance, the power consumption of the input LNA can be decreased and the overall power consumption of the channel is low. The prototype was implemented using a CMOS 0.13um standard process, and it occupies 400um x 400um. Simulations from extracted layout show very promising results. The power consumption of the complete channel for the signal tracking operations is 2.8uW, and is increased to 3.0uW when the feature extraction operation is performed, one of the lowest reported.

Today Chronic Heart Failure (CHF) represents one of leading cause of hospitalization among chronic disease, especially for elderly citizens, with a consequent considerable impact on patient quality of life, resources congestion and healthcare costs for the National Sanitary System. The current healthcare model is mostly in-hospital based and consists of periodic visits, but unfortunately it does not allow to promptly detect exacerbations resulting in a large number of rehospitalization. Recently physicians and administrators identify telemonitoring systems as a strategy able to provide effective and cost efficient healthcare services for CHF patients, ensuring early diagnosis and treatments in case of necessity. This work presents a complete and integrated ICT solution to improve the management of chronic heart failure through the remote monitoring of vital signs at patient home, able to connect in-hospital care of acute syndrome with out-of-hospital follow-up. The proposed platform represents the patient's interface, acting as link between biomedical sensors and the data collection point at the Hospital Information System (HIS) in order to handle in transparent way the reception, analysis and forwarding of the main physiological parameters.

The purpose of this document is to present a comparative study of five algorithms of heart sound localization, one of which, is a method based on radial basis function networks applied in a novel approach. The advantages and disadvantages of each method are evaluated according to a data base of 50 subjects in which there are 25 healthy subjects selected from the University Hospital of Strasbourg (HUS) and from theMARS500 project (Moscow) and 25 subjects with cardiac pathologies selected from the HUS. This study is made under the control of an experienced cardiologist. The performance of each method is evaluated by calculating the area under a receiver operating curve (AUC) and the robustness is shown against different levels of additive white Gaussian noise.

The understanding of neuronal function under the action of a certain stimulus can be facilitated using techniques to distinguish the potential action from different neurons. Thus, from simultaneous recording of multiple neurons one can determine the firing patterns of each of them. Usually these techniques are implemented in three stages. From raw electrical potentials recorded using an intracranial electrode, spikes are detected, then parameterized and finally sorted, attributing every single spike observed to a particular neuron. Recently, it was proposed an on-line sorting method based on the noise level. Nevertheless, sorting is done directly based on the raw samples. In this paper we introduce an alternative way using the modified Least Squares algorithm based on the priori error with error feedback to parameterize the raw signals before classification. Preliminary simulations results show that using parameters provides performance near to results where the sorting is done directly based on the raw samples.

Impedance spectroscopy is a common approach in assessing passive electrical properties of biological matter, however, serious problems appear in microfluidic devices in connection with distortion free signal acquisition from microelectrodes. The quality of impedance measurements highly depends on the presence of stray capacitances, signal distortions, and accompanying noises. Measurement deficiencies may be minimized with optimized electronics and sensing electrodes. The quality can further be improved with appropriate selection of measuring signals and also with selection of measuring methods such as a choice between current or voltage sources and between differential or singleended techniques. The microfluidic device that we present here incorporates an impedance sensor, which consists of an array of two sequential pairs of parallel microelectrodes, embedded in a microfluidic channel. All electronics and fluidic components are placed inside a metal holder, which ensures electric and fluidic connections to peripheral instruments. This configuration provides short electric connections and proper shielding. The method that we are using to evaluate the sample's impedance is the differential measurement technique, capable of suppressing the common mode signals and interferences, appearing in the signal-conditioning front-end circuit. Besides, it opens the possibility for compensating stray effects of the electrodes. For excitation we employ wideband signals, such as chirps or multifreqyency signals, which allow fast measurements, essential in the most impedimetric experiments in biology. The impedance spectra cover the frequency range between 10kHz - 10MHz. This is essential for accessing information relating to β-dispersion, which characterizes the cell's structural properties. We present two measurement schemes: (i) an in-phase differential method, which employs two transimpedance amplifiers, and (ii) an anti-phase method, which uses one transimpedance amplifier. In this study we analyze and compare the sensitivity, signal-to-noise-ratio, and operational bandwidths of these two methods against other commonly used related circuits.

Lab-on-a-chip systems have been attracting a growing attention for the perspective of miniaturization and portability of bio-chemical assays. Here we present a the design and characterization of a miniaturized, USB-powered, self-contained, 2-channel instrument for impedance sensing, suitable for label-free tracking and real-time detection of cells flowing in microfluidic channels. This original circuit features a signal generator based on a direct digital synthesizer, a transimpedance amplifier, an integrated square-wave lock-in coupled to a Σ▵ ADC converter, and a digital processing platform. Real-time automatic peak detection on two channels is implemented in a FPGA. System functionality has been tested with an electronic resistance modulator to simulate 1% impedance variation produced by cells, reaching a time resolution of 50μs (enabling a count rate of 2000 events/s) with an applied voltage as low as 200mV. Biological experiments have been carried out counting yeast cells. Statistical analysis of events is in agreement with the expected amplitude and time distributions. 2-channel yeast counting has been performed with concomitant dielectrophoretic cell separation, showing that this novel and ultra compact sensing system, thanks to the selectivity of the lock-in detector, is compatible with other AC electrical fields applied to the device.

In the 90s, efforts arise in the scientific world to automate and integrate one or several laboratory applications in tinny devices by using microfluidic principles and fabrication technologies used mainly in the microelectronics field. It showed to be a valid method to obtain better reactions efficiency, shorter analysis times, and lower reagents consumption over existing analytical techniques. Traditionally, these fluidic microsystems able to realize laboratory essays are known as Lab-On-a-Chip (LOC) devices. The capability to transport cells, bacteria or biomolecules in an aqueous medium has significant potential for these microdevices, also known as micro-Total-Analysis Systems (uTAS) when their application is of analytical nature. In particular, the technique of dielectrophoresis (DEP) opened the possibility to manipulate, actuate or transport such biological particles being of great potential in medical diagnostics, environmental control or food processing. This technique consists on applying amplitude and frequency controlled AC signal to a given microsystem in order to manipulate or sort cells. Furthermore, the combination of this technique with electrical impedance measurements, at a single or multiple frequencies, is of great importance to achieve novel reliable diagnostic devices. This is because the sorting and manipulating mechanism can be easily combined with a fully characterizing method able to discriminate cells. The paper is focused in the electronics design of the quadrature DEP generator and the four-electrode impedance measurement modules. These together with the lab-on-a-chip device define a full conception of an envisaged Point-of-Care (POC) device.

Cell-based assays for environmental monitoring enable quick information about a broad spectrum of possible contaminations. A key parameter that conveys information about the state of the cell culture is its electrical impedance, representing the amount of cell adhesion and morphological changes. We present a novel sensor for cell impedance measurements designed for application in a multi-parameter cell chip based on CMOS technology. A primary goal in the development of the sensor was keeping its interface to the external world as simple and robust as possible. This was achieved by integrating the sensor front-end electronics in close physical proximity to the sensing site. The result is a CMOS impedance-to-frequency converter with digital square wave output. A test chip featuring an array of 64 sensing microelectrodes, each addressable by a digital interface, was fabricated in a standard CMOS technology supplemented with a backend process for planar gold electrodes. We present measurement results with cells that demonstrate the successful operation of the system and its ability to capture changes in the cells' impedance caused by the model toxin cytochalasin.

Nanoscale sensors have the potential for ultrasensitive and highly parallel bioanalytical applications. Bottom up methods like gas-phase self assembly allow for the controlled and cost-efficient preparation of numerous functional units with nanometer dimensions. Their use in sensoric instruments, however, requires the defined integration into sensoric setups such as electrode arrays. We show here how to use alternating electrical fields (dielectrophoresis DEP) in order to address this micro nano integration problem. Nanoscale units such as metal nanoparticles or semiconductor nanowires are thereby polarized and moved into the direction of higher electrical field gradients. As result, these particles bridge an electrode gap and can so be used for electrical sensoric using the electrical resistance through this structure as value correlated to the presence of molecules at the sensor surface. In order to achieve high selectivity, capture molecules (such as complementary DNA or antibodies) are used.

Composite porous polysulfone-carbon nanotubes membranes were prepared by dispersing carbon nanotubes into a polysulfone solution followed by the membrane formation by phase inversion-immersion precipitation technique. The carbon nanotubes with amino groups on surface were functionalized with different enzymes (carbonic anhydrase, invertase, diastase) using cyanuric chloride as linker between enzyme and carbon nanotube. The composite membrane was used as a membrane reactor for a better dispersion of carbon nanotubes and access to reaction centers. The membrane also facilitates the transport of enzymes to active carbon nanotubes centers for functionalization (amino groups). The functionalized carbon nanotubes are isolated by dissolving the membranes after the end of reaction. Carbon nanotubes with covalent immobilized enzymes are used for biosensors fabrications. The obtained membranes were characterized by Scanning Electron Microscopy, Thermal analysis, FT-IR Spectroscopy, Nuclear Magnetic Resonance, and functionalized carbon nanotubes were characterized by FT-IR spectroscopy.

Coplanar waveguides fabricated on gold-doped Czochralski-silicon show reduced losses. Gold atoms implanted into silicon substrates compensate for background free carriers introduced by impurities in the material. This leads to an increased silicon resistivity which exhibits lower microwave absorption. High frequency measurements in 1-40 GHz range of coplanar waveguides fabricated on gold-doped silicon show attenuation reductions up to 70%, highlighting the benefits of deep level compensation of shallow level impurities in silicon using gold.

We discuss the applicability of using polymers for producing slot waveguide modes in single and triple-slot waveguide structures. We use finite element method to computationally study the field confinement and enhancement in the slot region with and without high refractive index coating on the top of the low index polymeric waveguide. The sensitivity to refractive index shift in ambient surrounding is improved almost five times in proposed high index coated polymer triple-slot waveguide structure compared to the ridge polymer waveguide.

We have proposed and modified a model of drying process of polymer solution coated on a flat substrate for flat polymer film fabrication supposing resist coating process in semiconductor engineering process and so on. And we have clarified dependence of distribution of polymer molecules on a flat substrate on a various parameters based on analysis of many numerical simulations of the model. Then we applied the model to thickness control of a thin film after drying through thermal management. But minute thickness control of a thin film after drying was not enough and more minute thickness control of it was desired. Therefore, in this study, we add evaporative management for more minute thickness control of a thin film after drying. As a result, thickness control of a thin film after drying in drying process of a polymer solution coated on a flat substrate can be improved further through adding evaporative operations to thermal operations artificially and instantaneously depending on solute's distribution during drying.

We show that by subjecting GaN epilayers on sapphire substrates to low-energy/low-dose ion treatment with subsequent photoelectrochemical etching it is possible to fabricate ultra-thin GaN membranes in the form of nano-roof hanging over networks of whiskers representing threading dislocations. The suspended membranes prove to be transparent to both UV-radiation and keV-energy electrons, their architecture being dependent upon the stirring conditions of the electrolyte during electrochemical etching. The obtained results are indicative of electrical conductivity, flexibility and excellent mechanical stability of ultra-thin GaN membranes characterized by prevailing yellow cathodoluminescence.

Nowadays, a lot of applications including nanoelectronics, spintronics or miniaturized sensors are using nanowires. Unfortunately, current techniques used for local synthesis of nanowires are still not fully compatible with common microfabrication techniques. In this study, we focus on the synthesis of patterned metallic nanowires by electrodeposition within nanoporous polyimide membranes integrated on 3 inch Si bulk wafers. Known to have a high planarization factor, a good resistance to most non-oxidizing acids and bases and to be CMOS compatible, polyimide is increasingly used in microsystems. Furthermore, like polycarbonate or polyester, nanoporous polyimide can be obtained by ion track-etching process. This polymer shows then a great interest to be used as a mold for nanowires growth. Patterned freestanding Nickel nanowires have been synthesized over a 100 nm thickness gold layer evaporated onto a SiO₂/Si substrate, with diameters of 20 and 60 nm, and length between 2 and 2.5 μm, depending on the electrodeposition time. Such fabrication process is promising to achieve more complex microelectromechanical systems incorporating nanostructures.

In our approach we are producing a polymer composite material with ZnO core spike particles as concave fillers. The core spike particles are synthesized by a high throughput method. Using PDMS (Polydimethylsiloxane) as a matrix material the core spike particles achieve not only a high mechanical reinforcement but also influence other material properties in a very interesting way, making such a composite very interesting for a wide range of applications. In a very similar synthesis route a nanoscopic ZnO-network is produced. As a ceramic this network can withstand high temperatures like 1300 K. In addition this material is quite elastic. To find a material with these two properties is a really difficult task, as polymers tend to decompose already at lower temperatures and metals melt. Especially under ambient conditions, often oxygen creates a problem for metals at these temperatures. If this material is at the same time a semiconductor, it has a high potential as a multifunctional material. Ceramic or classical semiconductors like III-V or IIVI type are high temperature stable, but typically brittle. This is different on the nanoscale. Even semiconductor wires like silicon with a very small diameter do not easily built up enough stress that leads to a failure while being bent, because in a first order approximation the maximum stress of a fiber scales with its diameter.

Nanoparticles are easily attracted by surfaces. This sticking behavior makes it difficult to clean contaminated samples. Some complex approaches have already shown efficiencies in the range of 90%. However, a simple and cost efficient method was still missing. A commonly used silicone for soft lithography, PDMS, is able to mold a given surface. This property was used to cover surface-bonded particles from all other sides. After hardening the PDMS, particles are still embedded. A separation of silicone and sample disjoins also the particles from the surface. After this procedure, samples are clean again. This method was first tested with carbon particles on Si surfaces and Si pillar samples with aspect ratios up to 10. Experiments were done using 2 inch wafers, which, however, is not a size limitation for this method.

Electrically Induced Bragg Reflectors can be very attractive to realize programable waveguides networks. Their practical realization is nevertheless intrinsically connected to the capability to make a peculiar comb-structure electrode on the top of the waveguides with typical period of 200 nm (corresponding to the Bragg length) and a tolerance of few nanometers. In this work, the experimental fabrication of these comb-structure electrodes by means of electron beam lithography is described. We fabricated large areas 1D periodic gold structures with nanometer resolution by using a high resolution electron beam lithography (EBL) process and a post-processing technique based on lift-off. These electrodes can be employed as Induced Bragg Reflectors in a multilayer structure for a not permanent periodically modulation of the effective refractive index of the guiding structure. The desired structures are obtained with nanometric resolution by means of EBL, digging furrows of rectangular section in both a polymetilmethacrylate (PMMA) and in α-chloromethacrylate and α-methylstyrene (ZEP) layer spin-coated on silicon, then evaporating a metal layer (Au) on the top and then by lift-off of metal. The EBL technique allows a very accurate control of the dielectric distribution of the exposed area able to produce feasible, high efficiency periodic and photonic band-gap structures. The resulting 1D gratings are made of metal lines 100 nm wide with a period of 200 nm and, 120 nm wide with a period of 250 nm, respectively. Large area structures (up to 1 mm x 6 μm) have been realized with nanometre resolution and they have been characterized by scanning electron microscopy (SEM). These structures will be used in a future work of ours to realize 40 GHz switching speed modulator by inducing a Bragg Reflector with a reverse biased vertical InP/InGaAsP p-i-n diode according to the predictions of the grating reflectivity spectra and of the transient response.

We proposed the photonic crystal coupled surface plasmon resonance sensors using gold nano-structure to enhance the sensitivity of an SPR sensor. The proposed configuration with the photonic crystal structure is Au(Photonic crystal)/Au/Ag/Cr/Glass. The 20 nm silver film and the 20 nm gold film are layered on the glass substrate. Then, the dot-like gold photonic crystal structures with a period pitch are patterned on the Au/Ag/Cr/Glass structure. The reflectance and the optical-mode propagations as a function of incident angle are calculated using the three-dimensional finite-difference time-domain method. Under this resonance condition, the incident light is highly absorbed and loses a fair amount of its energy, which results in a dip in the intensity profile of the reflected light. The optimum resonance angle of 44.5 degrees is obtained in the 75-nm-radius Au photonics crystal structure with a period of 300 nm.