AJAY KUMAR SINGH
@niituniversity.in
Professor
NIIT University Neemarana Rajasthan India
RESEARCH INTERESTS
VLSI design
Renewable energy
Modeling of MOS devices
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Sachin Verma and Ajay Singh
Springer Science and Business Media LLC
Shubham Patil, Anand Sharma, R. Gaurav, Abhishek Kadam, Ajay Kumar Singh, Sandip Lashkare, Nihar Ranjan Mohapatra, and Udayan Ganguly
Institute of Electrical and Electronics Engineers (IEEE)
Compact and energy-efficient synapse and neurons are essential to realize the full potential of neuromorphic computing. In addition, a low variability is indeed needed for neurons in deep neural networks for higher accuracy. Further, process (P), voltage (V), and temperature (T) (PVT) variation are essential considerations for low-power circuits as performance impact and compensation complexities are added costs. Recently, band-to-band tunneling (BTBT) neuron has been demonstrated to operate successfully in a network to enable a liquid state machine (LSM). A comparison of the PVT with competing modes of operation (e.g., BTBT versus subthreshold and above threshold) of the same transistor is a critical factor in assessing performance. In this work, we demonstrate the PVT variation impact on the BTBT regime and benchmark the operation against the subthreshold regime (SS) and ON-regime (<inline-formula> <tex-math notation="LaTeX">$\\text{I}_{ \\mathrm{\\scriptscriptstyle ON}}$ </tex-math></inline-formula>) of partially depleted silicon-on-insulator MOSFET. It is shown that the ON-state regime offers the lowest variability but dissipates higher power, hence not usable for low-power sources. Among the BTBT and SS regimes, which can enable the low-power neuron, the BTBT regime has shown <inline-formula> <tex-math notation="LaTeX">$\\sim 3\\,\\,{\\times }$ </tex-math></inline-formula> variability reduction (<inline-formula> <tex-math notation="LaTeX">${ \\boldsymbol {\\sigma }_{I{_{D}}}{/} \\boldsymbol {\\mu }_{I{_{D}}}}$ </tex-math></inline-formula>) compared to the SS regime, considering the cumulative PVT variability. The improvement is due to the well-known weaker P, V, and T dependence of BTBT versus SS. We show that the BTBT variation is uncorrelated with mutually correlated SS and <inline-formula> <tex-math notation="LaTeX">$\\text{I}_{{ \\mathrm{\\scriptscriptstyle ON}}}$ </tex-math></inline-formula> operation—indicating its different origin from the mechanism and location perspectives. Hence, the BTBT regime is promising for low-current, low-power, and low device-to-device (D2D) variability neuron operation.
Minakshi Koundal, Ajay Kumar Singh, and Chhaya Sharma
Emerald
Purpose This paper aims to investigate the eco-friendly neodymium tartrate (NdTar) inhibitor for mild steel in sodium chloride (NaCl) solution. Design/methodology/approach The mild steel 1010 coupon was considered for the current study. Weight loss and the electrochemical methods were used to evaluate the inhibitory effects of neodymium chloride (NdCl3) and NdTar on mild steel in NaCl solution. Scanning electron microscopy, energy-dispersive X-ray analysis and attenuated total reflectance-Fourier transform infrared spectroscopy measurements were carried out to study the morphology and composition of the film, nature of deposits and corrosion products formed in test media on the corroded steel, with the objective of further analyzing the observed behavior of the two inhibitors. Findings Of the two, NdTar performs better than NdCl3 because it shields mild steel surfaces for longer. According to the results, when NdCl3 is present in a corrosive solution, the protective film only comprises Nd/Fe oxide/hydroxide/carbonate. However, when neodymium is coupled with the tartrate group (an organic group) and then added to the NaCl solution, the inhibitor film comprises both bimetallic complexes (Fe-Tar-Nd) and metal oxide/hydroxide/carbonate, which results in a more compact film and has higher inhibition efficiency. Originality/value This study evaluated the combined effects of inorganic and organic inhibitors with those of an inorganic inhibitor used alone for mild steel in NaCl solution.
Abhishek A. Kadam, Ajay K. Singh, Laxmeesha Somappa, Maryam Shojaei Baghini, and Udayan Ganguly
Institute of Electrical and Electronics Engineers (IEEE)
Continuous-time filters with low-frequency cutoff are crucial building blocks in analog signal processing circuits for speech processing and biomedical applications. The design of an integrated continuous-time filter with a cutoff frequency spanning from sub-Hz to a few kHz is constrained by the ultra-low power and area minimization requirement. In this brief, we have experimentally demonstrated a low pass filter response using only a single partially depleted (PD) silicon on insulator (SOI) transistor. The proposed novel filter is based on band to band tunnelling (BTBT). This low pass filter is on-chip tunable to provide a wide cutoff frequency ranging from 2 Hz to 20 kHz, with a silicon footprint of $9 \\mathbf {\\mu m^{2}}$ and the maximum power consumption of 0.6 nW in Global Foundries’ (GF) 45 nm RFSOI technology. The proposed tunneling-based filter is less prone to process variations and mismatches as compared to traditional integrated analog filters. The proposed BTBT-based passive RC filter with spurious free dynamic range (SFDR) of 29 dbc, outperforms previously reported filters in the literature in terms of power consumption and area. The ultra-low power consumption and area efficiency make this proposed low pass filter suitable for the multichannel analog front-end low-frequency filters for noise-tolerant neural network-based applications such as speech recognition and electrophysiological signal recognition.
Shankar Kesarwani, Nandhini Swaminathan, Ajay Singh, Dipankar Saha, and Swaroop Ganguly
American Chemical Society (ACS)
Sachin Verma and Ajay Singh
Wiley
Herein, an analytical study of a strongly correlated quantum dot‐based thermoelectric particle‐exchange heat engine for both finite and infinite on‐dot Coulomb interaction is presented. Employing Keldysh's nonequilibrium Green's function formalism for different decoupling schemes in the equation of motion, the thermoelectric properties within the nonlinear transport regime have been analyzed. Initially, Hubbard‐I approximation has been used to study the quantum dot level position (), thermal gradient (), and on‐dot Coulomb interaction (U) dependence of the thermoelectric properties. Furthermore, as a natural extension, a decoupling beyond Hubbard‐I (Lacroix approximation) with infinite‐U limit (strong on‐dot Coulomb repulsion) has been used to provide additional insight into the operation of a more practical quantum dot heat engine. Within this infinite‐U limit, the role of the symmetric dot‐reservoir tunneling (Γ) and external serial load resistance (R) in optimizing the performance of the strongly correlated quantum dot heat engine is examined. The infinite‐U results show a good quantitative agreement with recent experimental data for a quantum dot coupled to two metallic reservoirs.
Abhishek A. Kadam, Anmol Biswas, Vivek Saraswat, Ajay K. Singh, Laxmeesha Somappa, Maryam Shojaei Baghini, and Udayan Ganguly
IEEE
Liquid State Machine (LSM) is a brain-inspired neural network architecture for solving temporal classification problems like speech recognition. The simple structure of LSM with a reservoir and single-layer classifier is attractive from a hardware implementation perspective. When the LSM is considered for low-power hardware implementation in real-world command word recognition tasks, challenges like nonidealities in sensor filter response and ambient noise become critical concerns. In this work, we evaluate the performance of LSM based on two aspects (1) ambient noise and (2) sensor/preprocessing circuit nonidealities. For Ambient noise, we use additive white gaussian noise (AWGN) and ambient noise using the iNoise Indian Noise dataset that covers various natural indoor, outdoor, and travel-related environmental sounds. To understand the impact of input hardware nonidealities, we analyzed the impact of the audio preprocessing filter's quality factor, order, center frequency variations, and output nonlinearity on LSM performance. We use the spoken digits classification in the TI-46 dataset. This paper's findings present design guidelines for the system designers intending to use liquid-state machines for speech classification tasks. In terms of filter design, first, there is a broad Q, order space for filter design where performance is high. We use the hardware-friendly parallel 4th order Butterworth bandpass filter model to provide a baseline 98% accuracy in speech classification tasks. Second, the performance of LSM degrades proportionally to the variation in the center frequency of the bandpass filters in the filter bank. Third, nonlinearity with the third-order harmonic of 50 dBc can be tolerated. Regarding ambient noise, our study shows that a 40 dB SNR for AWGN is sufficient for ideal performance. Second, the best case of “home” noise leads to a performance of 91.4%. Outdoor and travel noise reduce the classification performance to 78.8% and 62.4%, respectively. However, ideal performance is recovered if the signal to noise ratio (SNR) is increased, particularly by 10 dB in indoor conditions and 30 dB in outdoor conditions. Thus, our study presents an engineering evaluation for real-world spoken digit recognition using LSMs.
Shubham Patil, Jayatika Sakhuja, Ajay Kumar Singh, Anmol Biswas, Vivek Saraswat, Sandeep Kumar, Sandip Lashkare, and Udayan Ganguly
IEEE
Energy-efficient real-time synapses and neurons are essential to enable large-scale neuromorphic computing. In this paper, we propose and demonstrate the Schottky-Barrier MOSFET-based ultra-low power voltage-controlled current source to enable real-time neurons for neuromorphic computing. Schottky-Barrier MOSFET is fabricated on a Silicon-on-insulator platform with polycrystalline Silicon as the channel and Nickel/Platinum as the source/drain. The Poly-Si and Nickel make the back-to-back Schottky junction enabling ultra-low ON current required for energy-efficient neurons.
Usha Pandey, A.K. Singh, and Chhaya Sharma
Elsevier BV
Ajay Kumar Singh, Vivek Saraswat, Maryam Shojaei Baghini, and Udayan Ganguly
Institute of Electrical and Electronics Engineers (IEEE)
Low-power and low-area neurons are essential for hardware implementation of large-scale SNNs. Various novel-physics-based leaky-integrate-and-fire (LIF) neuron architectures have been proposed with low power and area, but are not compatible with CMOS technology to enable brain scale implementation of SNN. In this paper, for the first time, we demonstrate hardware implementation of recurrent SNN using proposed low-power, low-area, and low-leakage band-to-band-tunneling (BTBT) based neurons. A low-power thresholding circuit is proposed. We further propose a predistortion technique to linearize a nonlinear neuron without any area and power overhead. We establish the equivalence of the proposed neuron with the ideal LIF neuron to demonstrate its versatility. The tunneling regime enables a high input impedance in the BTBT neurons (few $\\text{G}\\Omega$ ) to enable a voltage input without loading the synaptic array. To verify the effect of the proposed neuron, a 36-neuron recurrent SNN is fabricated in GF-45nm PDSOI technology. We achieved 5000x lower energy-per-spike at a similar area and 10x lower standby power at a similar area and energy-per-spike. Such overall performance improvement enables brain scale computing.
Sachin Verma and Ajay Singh
IOP Publishing
Abstract A detailed investigation of the non-equilibrium steady-state electric and thermoelectric transport properties of a quantum dot (QD) coupled to the normal metallic and s-wave superconducting reservoirs (N–QD–S) are provided within the Coulomb blockade regime. Using non-equilibrium Keldysh Green’s function formalism, initially, various model parameter dependences of thermoelectric transport properties are analysed within the linear response regime. It is observed that the single-particle tunnelling close to the superconducting gap edge can generate a relatively large thermopower and figure of merit. Moreover, the Andreev tunnelling plays a significant role in the suppression of thermopower and figure of merit within the gap region. Further, within the non-linear regime, we discuss two different situations, i.e., the finite voltage biasing between isothermal reservoirs and the finite thermal gradient in the context of thermoelectric heat engine. In the former case, it is shown that the sub-gap Andreev heat current can become finite beyond the linear response regime and play a vital role in asymmetric heat dissipation and thermal rectification effect for low voltage biasing. The rectification of heat current is enhanced for strong on-dot Coulomb interaction and at low background thermal energy. In the latter case, we study the variation of thermovoltage, thermopower, maximum power output, and corresponding efficiency with the applied thermal gradient. These results illustrate that hybrid superconductor–QD nanostructures are promising candidates for the low-temperature thermal applications.
Minakshi Koundal, A.K. Singh, and Chhaya Sharma
Elsevier BV
Vipin Choudhary, Rajendra Kumar, Vijay Kumar, and A.K. Singh
IOP Publishing
Abstract Corrosion in paper industries is responsible not only for weakening of metal structures but also for pollution of process liquors and contamination of products. The bleaching sections in pulp and paper industry are among the worst affected by the ravages of corrosion. In bleach plants the materials are exposed to highly corrosive bleaching liquors. Now day’s new norms of safety of environment are forcing paper industries to use peroxide as a bleaching agent instead of chlorine. So in the present study an effort has been done to propose an appropriate material for the construction of future bleach plants keeping in mind their mechanical factors and cost of the material. Accordingly electrochemical polarization tests, E vs. time curve, potentiodynamic polarization curve and cyclic polarization curve were performed on stainless steels samples of 316L, 317L, 2205 and 254SMO in peroxide containing solutions having H2O2, 500 and 1000 parts per million (ppm). The pH of these solutions was kept 4. The Chloride content varied from 0 to 1000 ppm. These tests was performed at room temperature. These tests showed increased resistance against corrosion in order of: 316L<317L<2205<254SMO. Thus 254SMO shows highest resistance for attack of corrosion but keeping in mind fabrication and cost aspects optimal material for treating these peroxide media is recommended to be SS 2205.
Reena Sachan, Ajay Kumar Singh, and Yuvraj Singh Negi
Springer Science and Business Media LLC
Reena Sachan and Ajay Kumar Singh
Elsevier BV
Laxmeesha Somappa, Adarsh G. Menon, Ajay K. Singh, Ashwin A. Seshia, and Maryam Shojaei Baghini
Institute of Electrical and Electronics Engineers (IEEE)
This article presents a portable and programmable frequency measurement system (PrO-FMS) with 0.1-ppm RMSE resolution over a measurement time interval of 33.2 s for bulk-acoustic resonator applications. PrO-FMS has a feature of choosing a frequency estimation method and accordingly the sampling frequency, which is programmable. Five frequency estimation methods, Candan, Djukanovic, Prony, M-Pisarenko, and zero crossing interpolation methods, are reviewed for high-resolution frequency measurement. PrO-FMS can also be reconfigured to select a particular resonance mode over a range of 1–10 MHz. Measurement results are provided for two different commercial quartz crystals and a microfabricated in-plane bulk acoustic resonator in two different modes of resonance. The results of these estimation methods are compared with a standard commercial tabletop frequency counter. Measurement results show that PrO-FMS can achieve a resolution of 0.1 ppm RMSE. For the same gate time, PrO-FMS provides better resolution than standard tabletop frequency counter. This article also provides a study on the behavior of the five different frequency estimation methods for short- and long-term measurements for quartz crystals and bulk acoustic resonator in two different modes.
S Pande, S Balanethiram, A K Singh, M Gupta, B Umapathi, H S Jatana, N Mohapatra, and A Chakravorty
IEEE
BiCMOS technology enables VLSI circuits with high current driving capability and optimized speed-power-density performance when compared to standalone bipolar or CMOS technologies. In this work, we present the device design, process development and optimization of diffusion poly-emitter bipolar junction transistor (BJT), for the first time in India, for analog and RF applications. The baseline 180 nm CMOS process of Semi-Conductor Lab at Chandigarh (India) is used to develop the BiCMOS process. All the TCAD simulations are calibrated with the measured data of baseline BJT from 180 nm CMOS process. Calibrated simulations of our proposed poly-emitter BJT show current gain > 140 and current driving capacity > 10 mA. The breakdown voltage of the transistor is above 5 V ($\\text{BV}_{CEO}$) with cut-off frequency ($f_{T}$) and maximum oscillation frequency ($f_{max}$) more than 17 GHz and 40 GHz, respectively.
S Balanethiram, S Pande, A K Singh, B Umapathi, H S Jatana, N Mohapatra, and A Chakravorty
IEEE
It is well known that combining the benefits of bipolar and CMOS (Complementary Metal Oxide Semiconductor) devices in BiCMOS technology, one can achieve better speed and power-density in microelectronic circuitry. In this work, we present the device design, process development and optimization of diffusion bipolar junction transistor (BJT), for the first time in India, for analog and RF applications. The baseline 180nm CMOS process of Semi-Conductor Lab (SCL) at Chandigarh is used to develop the BiCMOS process. All the TCAD simulations are calibrated with the measured data of baseline BJT from 180nm CMOS process with two different process splits. Calibrated simulations of our proposed silicon BJT show current gain > 90 and current driving capacity > 10 mA. The breakdown voltage of the transistor is above 25 V (BVCB0) with cut-off frequency (fT) and maximum oscillation frequency (fmax) more than 5 GHz and 3 GHz, respectively.
Reena Sachan and Ajay Kumar Singh
Emerald
PurposeThe purpose of this study is to investigate microbial influenced corrosion of steel because of iron oxidizing bacteria (IOB).Design/methodology/approachCarbon steel was selected for this study. Winogradsky media was used for isolation of IOB and as test solution for corrosion measurements. Electrochemical tests and immersion test were conducted to estimate the corrosion rate and extent of pitting. The corroded surface was analysed by SEM and corrosion products formed over the metal surface were identified by XRD and Fourier transformed infrared. Biofilm formed over the corroded metal was analysed by UV-visible spectroscopy for its extracellular polymeric substances (EPS) constituents.FindingsPresence of IOB in Winogradsky medium enhances corrosion. Uniform and localized corrosion increases with increased bacterial concentration and EPS constituents of the biofilm. Iron sulphite formation as one of the corrosion products has been suggested to be responsible for increased corrosion attack in the inoculated media in comparison to control media where corrosion product observed is iron hydrogen phosphate which is protective in nature.Originality/valueThis work correlates increased corrosion of steel in the presence of bacteria with the nature of corrosion products formed over it in case of IOB. Formation of corrosion products is governed by various electrochemical reactions; hence, inhibition of such reactions may lead to reduce or stop the formation of such products which enhances corrosion and thereby may reduce the extent of microbial induced corrosion.