A low-noise low-power noise-adaptive neural amplifier in 0.13um CMOS technology

Chronic recording of neural signals is indispensable in designing efficient brain machine interfaces and in elucidating human neurophysiology. The advent of multichannel microelectrode arrays has driven the need for electronics to record neural signals from many neurons. The dynamic range of the system is limited by background system noise which varies over time. We propose a neural amplifier in UMC 130 nm, 2P8M CMOS technology. It can be biased adaptively from 200 nA to 2 uA, modulating input referred noise from 9.92 uV to 3.9 uV. We also describe a low noise design technique which minimizes the noise contribution of the load circuitry. The amplifier can pass signal from 5 Hz to 7 kHz while rejecting input DC offsets at electrode-electrolyte interface. The bandwidth of the amplifier can be tuned by the pseudo-resistor for selectively recording low field potentials (LFP) or extra cellular action potentials (EAP). The amplifier achieves a mid-band voltage gain of 37 dB and minimizes the attenuation of the signal from neuron to the gate of the input transistor. It is used in fully differential configuration to reject noise of bias circuitry and to achieve high PSRR.

Identification of coherent synchronous generators in a multi- machine power system using support vector clustering

This paper illustrates the application of a new technique, based on Support Vector Clustering (SVC) for the direct identification of coherent synchronous generators in a large interconnected Multi-Machine Power Systems. The clustering is based on coherency measures, obtained from the time domain responses of the generators following system disturbances. The proposed clustering algorithm could be integrated into a wide-area measurement system that enables fast identification of coherent clusters of generators for the construction of dynamic equivalent models. An application of the proposed method is demonstrated on a practical 15 generators 72-bus system, an equivalent of Indian Southern grid in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations on coherency are also investigated.

Interface capturing simulations of acoustically driven bubble dynamics in and near tissue

Tissue injury during therapeutic ultrasound or lithotripsy is thought, in cases, to be due to the action of cavitation bubbles. Assessing this and mitigating it is challenging since bubble dynamics in the complex confinement of tissues or in small blood vessels are challenging to predict. Simulations tools require specialized algorithms to simultaneously represent strong acoustic waves and shocks, topologically complex liquid‐vapor phase boundaries, and the complex viscoelastic material dynamics of tissue. We discuss advances in a simulation tool for such situations. A single‐mesh Eulerian solver is used to solve the governing equations. Special sharpening terms maintain the liquid‐vapor interface in face of the finite numerical dissipation included in the scheme to accurately capture shocks. A recent enhancement to this formulation has significantly improved this interface capturing procedure, which is demonstrated for simulation of the Rayleigh collapse of a bubble. The solver also transports elastic stresses and can thus be used to assess the effects of elastic properties on bubble dynamics. A shock‐induced bubble collapse adjacent to a model elastic tissue is used to demonstrate this and draw some conclusions regarding the injury suppressing role that tissue elasticity might play.

Microscopic dynamics of nanoparticle monolayers at air-water interface

We present results of surface mechanical and particle tracking measurements of nanoparticles trapped at the air-water interface as a function of their areal density. We monitor both the surface pressure (II) and isothermal compression modulus (epsilon) as well as the dynamics of nanoparticle clusters, using fluorescence confocal microscopy while they are compressed to very high density near the two dimensional close packing density Phi similar to 0.82. We observe non-monotonic variation in both epsilon and the dynamic heterogeneity, characterized by the dynamical susceptibility chi(4) with Phi, in such high density monolayers. We provide insight into the underlying nature of such transitions in close packed high density nanoparticle monolayers in terms of the morphology and flexibility of these soft colloidal particles.. We discuss the significance our results in the context of related studies on two dimensional granular or colloidal systems. (C) 2013 Elsevier Inc. All rights reserved.

Support vector machine based high speed protection relay for EHV/UHV transmission line

This paper presents a fast and accurate relaying technique for a long 765kv UHV transmission line based on support vector machine. For a long EHV/UHV transmission line with large distributed capacitance, a traditional distance relay which uses a lumped parameter model of the transmission line can cause malfunction of the relay. With a frequency of 1kHz, 1/4th cycle of instantaneous values of currents and voltages of all phases at the relying end are fed to Support Vector Machine(SVM). The SVM detects fault type accurately using 3 milliseconds of post-fault data and reduces the fault clearing time which improves the system stability and power transfer capability. The performance of relaying scheme has been checked with a typical 765kV Indian transmission System which is simulated using the Electromagnetic Transients Program(EMTP) developed by authors in which the distributed parameter line model is used. More than 15,000 different short circuit fault cases are simulated by varying fault location, fault impedance, fault incidence angle and fault type to train the SVM for high speed accurate relaying. Simulation studies have shown that the proposed relay provides fast and accurate protection irrespective of fault location, fault impedance, incidence time of fault and fault type. And also the proposed scheme can be used as augmentation for the existing relaying, particularly for Zone-2, Zone-3 protection.

Effect of Stress and Interface defects on Photo Luminescence of Si nano-crystals embedded in SiO2

Effect of stress and interface defects on photo luminescence property of a silicon nano-crystal (Si-nc) embedded in amorphous silicon dioxide (a-SiO2) are studied in this paper using a self-consistent quantum-continuum based modeling framework. Si-ncs or quantum dots show photoluminescence at room temperature. Whether its origin is due to Si-nc/a-SiO2 interface defects or quantum confinement of carriers in Si-nc is still an outstanding question. Earlier reports have shown that stresses greater than 12 GPa change the indirect energy band gap structure of bulk Si to a direct energy band gap structure. Such stresses are observed very often in nanostructures and these stresses influence the carrier confinement energy significantly. Hence, it is important to determine the effect of stress in addition to the structure of interface defects on photoluminescence property of Si-nc. In the present work, first a Si-nc embedded in a-SiO2 is constructed using molecular dynamics simulation framework considering the actual conditions they are grown so that the interface and residual stress in the structure evolves naturally during formation. We observe that the structure thus created has an interface of about 1 nm thick consisting of 41.95% of defective states mostly Sin+ (n = 0 to 3) coordination states. Further, both the Si-nc core and the embedding matrix are observed to be under a compressive strain. This residual strain field is applied in an effective mass k.p Hamiltonian formulation to determine the energy states of the carriers. The photo luminescence property computed based on the carrier confinement energy and interface energy states associated with defects will be analysed in details in the paper.

Interface characterization of Co2MnGe/Rh2CuSn Heusler multilayers

To address the amount of disorder and interface diffusion induced by annealing, all-Heusler multilayer structures, consisting of ferromagnetic Co2MnGe and nonmagnetic Rh2CuSn layers of varying thicknesses, have been investigated by means of hard x-ray photoelectron spectroscopy and x-ray magnetic circular dichroism. We find evidence for a 4 angstrom thick magnetically dead layer that, together with the identified interlayer diffusion, are likely reasons for the unexpectedly small magnetoresistance found for current-perpendicular-to-plane giant magnetoresistance devices based on this all-Heusler system. We find that diffusion begins already at comparably low temperatures between 200 and 250 degrees C, where Mn appears to be most prone to diffusion.

Near infrared detectors based on HgSe and HgCdSe quantum dots generated at the liquid-liquid interface

HgSe and Hg0.5Cd0.5Se quantum dos (QDs) are synthesized at room temperature by a novel liquid-liquid interface method and their photodetection properties in the near-IR region are investigated. The photodetection properties of our Te-free systems are found to be comparable to those of the previously reported high performance QD vis-IR detectors including HgTe. The present synthesis indicates the cost-effectiveness of selenium based IR detectors owing to the abundance and lower toxicity of selenium compared to tellurium.

Support vector clustering-based direct coherency identification of generators in a multi-machine power system

This study investigates the application of support vector clustering (SVC) for the direct identification of coherent synchronous generators in large interconnected multi-machine power systems. The clustering is based on coherency measure, which indicates the degree of coherency between any pair of generators. The proposed SVC algorithm processes the coherency measure matrix that is formulated using the generator rotor measurements to cluster the coherent generators. The proposed approach is demonstrated on IEEE 10 generator 39-bus system and an equivalent 35 generators, 246-bus system of practical Indian southern grid. The effect of number of data samples and fault locations are also examined for determining the accuracy of the proposed approach. An extended comparison with other clustering techniques is also included, to show the effectiveness of the proposed approach in grouping the data into coherent groups of generators. This effectiveness of the coherent clusters obtained with the proposed approach is compared in terms of a set of clustering validity indicators and in terms of statistical assessment that is based on the coherency degree of a generator pair.

An early in-situ stress signature of the AlN-Si pre-growth interface for successful integration of nitrides with (111) Si

The integration of Metal Organic Chemical Vapor Deposition (MOCVD) grown group III-A nitride device stacks on Si (111) substrates is critically dependent on the quality of the first AlN buffer layer grown. A Si surface that is both oxide-free and smooth is a primary requirement for nucleating such layers. A single parameter, the AlN layer growth stress, is shown to be an early (within 50 nm), clear (<0.5 GPa versus > 1GPa), and fail-safe indicator of the pre-growth surface, and the AlN quality required for successful epitaxy. Grain coalescence model for stress generation is used to correlate growth stress, the AlN-Si interface, and crystal quality. (C) 2013 AIP Publishing LLC.

A Committee Machine Approach for Compressed Sensing Signal Reconstruction

Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.

Mechanical and thermal modeling of In-Cu composites for thermal interface materials applications

In-Cu composite solders have been proposed as an effective thermal interface material. Here, finite element analysis and theoretical treatment of their mechanical and thermal behavior is presented. It was determined that the stresses and the strains were concentrated in the narrow and wider In channels, respectively. Furthermore, it is suggested that an In-Cu composite with disk-shaped Cu inclusions may not only further improve the thermal conductivity but may also reduce the stiffness of In-Cu composites in shear.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.

Effect of Post-Deposition Annealing on the Al2O3/Si(100) Interface Properties

In the present investigation, Al2O3 thin films were deposited onto Si < 100 > substrates by DC reactive magnetron sputtering. The films were annealed in vacuum for one hour at 623, 823 and 1023 K. The composition of the films was quantitatively estimated using X-ray photoelectron spectroscopy (XPS) and the O/Al ratio was found be in the range 1.19 to 1.43. Grazing incidence X-ray diffraction (GIXRD) results revealed that the annealed films are amorphous in nature. Cross sectional transmission electron microscopy (X-TEM) analysis was carried out to study the microstructure and nature of the Al2O3-Si interface as a function of post-deposition annealing. TEM results revealed the presence of nanocrystalline gamma-Al2O3 in the annealed films and an amorphous interface layer was observed at the Al2O3 Si interface. The thickness of the amorphous interface layer was determined from the TEM analysis and the results are discussed.