CASTAM: A process variation analysis simulator for MOS LSI's

A generalized technique is proposed for modeling the effects of process variations on dynamic power by directly relating the variations in process parameters to variations in dynamic power of a digital circuit. The dynamic power of a 2-input NAND gate is characterized by mixed-mode simulations, to be used as a library element for 65nm gate length technology. The proposed methodology is demonstrated with a multiplier circuit built using the NAND gate library, by characterizing its dynamic power through Monte Carlo analysis. The statistical technique of response surface methodology (RSM) using design of experiments (DOE) and least squares method (LSM), are employed to generate a for gate power to account for simultaneous variations in multiple process parameters. We demonstrate that our hybrid model based statistical design approach results in considerable savings in the power budget of low power CMOS designs with an error of less than 1%, with significant reductions in uncertainty by at least 6X on a normalized basis, against worst case design

More than forty years ago, Professor Chua predicted the existence of the memristor to complete the set of passive devices that previously includes only resistor, capacitor, and inductor. However, till 2008 the first physical realization of memristors was demonstrated by HP Lab. The unique properties of memristor create great opportunities in future system design. For instance, the memristor has demonstrated the similar function as synapse, which makes it promising in neuromorphic circuits design. However, as a nano-scale device, the process variation control in the manufacturing of memristors is very difficult. The impact of the process variations on a neural network system that relies on the continuous (analog) states of the memristor could be significant due to the deviation of the memristor state from the designed value. So a complete process variation analysis on memristor is necessary for the application in neural network. Due to the different physical mechanisms, TiO2-based memristor and spintronic memristor demonstrate very different electrical characteristics even when exposing the two types of devices to the same excitations and under the same process variation conditions. In this work, the impact of different geometry variations on the electrical properties of these two different types of memristors was evaluated by conducting the analytic modeling analysis and Monte-Carlo simulations. A simple algorithm, which is based on the latest characterization method of LER (line edge roughness) and thickness fluctuation problems, was proposed to generate a large volume of geometry variation-aware three-dimensional device structures for Monte-Carlo simulations. We investigate the different responses of the static and memristive parameters of the two devices and analyze its implication to the electrical properties of the memristors. Furthermore, a process-variation aware device model can be built based on our work. Both corner model and statistical model can be provided depending on users’ requirements. Our device models make it possible for scientists and engineers to design neuromorphic circuits with memristive devices, and therefore, to convert virtual neural network in super computer to the real hardware memristive system in the future. Rather than the existing crossbar-based neuron network designs, we focus on memristor-based synapse and the corresponding training circuit to mimic the real biological system. The basic synapse design is presented, and the training sharing scheme and explore design implication on multi-synapse neuron system have been explored.

A practical supply current test method is proposed and the experimental evaluation results are presented. In the method, the unit-to-unit variation of electrical characteristics in each logic gate is modeled as a Gaussian distribution and faults are detected with a statistical hypothesis technique.

In this paper the analysis of SNM, RNM, WNM and static power variation with width of access, load and driver have been carried out for nanoscale FinFET based SRAM cell. FinFET based SRAM design has been proposed as an alternative solution to the bulk devices. It can be inferred from the results that with increase in the width of driver FinFET, the high SNM reduces and low SNM increases. This is due the fact that the leakage current is considerably reduced due to increased control of the FinFET device structure, resulting relatively in highI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</sub> /I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</sub> ratio. Further, the effect of process variation on the SRAM cell performance was analyzed using Monte Carlo simulation on HSPICE. The Monte Carlo simulation results for RNM and WNM to quantify the effect of process variation arising due to variation in FinFET's widths. The simulation was carried out for 1000 values, assuming 3σ equal to 10% of the mean value. Two structures of the FinFET viz. the standard PTM model and an underlapped FinFET have been also used for the simulations. It was identified that while the relative levels of the noise margins were lower for the underlapped case, the standard deviation was considerably lower too. In this work we also analyze the effect of temperature on noise margins and static power for FinFET based SRAM cell. FinFET is suitable for future nanoscale memory circuits design due to its reduced Short Channel Effects (SCE) and leakage current.

In this article, an explicit formula is derived for determining appropriate number of simulation runs to estimate the parametric yield or violation probability of VLSI circuits. The formula involves no approximation and thus offers a rigorous control of the statistical error of estimation. Moreover, the formula is substantially less conservative than existing methods and hence can be used to avoid unnecessary computation. The application of the formula is illustrated by the timing analysis of an <i>n</i>-input NAND gate with a capacitive load.

Structural and electrical characteristics of double perovskite: Nd2CoMnO6

A series of experiments were conducted on multilayer sintering of MnZn ferrite cores in a production type furnace. The cup cores were stacked one over the other, up to ten layers and each loading of the furnace had 3000 cup cores 18×11mm in size. All the electrical characteristics such as permeability, resistivity, eddy current and hysterisis loss, disaccommodation and temperature factor were measured. There was no significant difference between layers in these factors. Experimental data supporting these observations are presented. Production runs were undertaken and the experimental findings were confirmed. It is suggested that the soaking time of one and a half hr and slower cooling rate has helped to attain equilibrium conditions allowing the gases to permeate to all the layers. The variation in electrical characteristics that are evident appears to be due to the inherent limitations in process control.

Winner-Take- All (WTA) circuit chooses a winner input from a set of input signals. WTA circuits employ transistors that operate in the sub-threshold or weak inversion region. With technology scaling, sub-threshold circuits are prone to mismatch and process variations which degrade the performance of these circuits. This paper presents a novel WTA circuit that employs a CMOS double pair transistor as a translinear element that is more tolerant to mismatch and process variations. Monte Carlo simulations are used to compare the performance of the existing and the proposed topologies to estimate the effects of process and mismatch variations. Results show that the proposed circuit is able to reduce the range of variations by three orders of magnitude compared to original one for similar variations in the transistor parameters. The proposed element also shows better accuracy in replicating the maximum input current compared to the original circuit.

As energy demand increases and global warming progresses, expectations for fuel cells, which generate electricity through chemical reactions between hydrogen and oxygen, are rising. There are various types of fuel cells, which are classified according to the electrolyte. Polymer electrolyte fuel cells (PEFCs) are expected to be used in stationary power sources for home use and fuel cell vehicles because of their low operating temperature, short start-up time, and ease of miniaturization. The cost has been an issue in the widespread use of fuel cells. The amount of platinum used in the catalyst layer (CL) must be reduced to reduce costs. However, it increases the current density per unit area of platinum. There are three factors that contribute to voltage drop: ohmic polarization, activation polarization, and diffusion polarization. At high current densities, the voltage drop due to diffusion polarization is dominant. The main cause of diffusion polarization is the transport resistance of oxygen molecules in the CL, and improving the oxygen transport properties in the CL will lead to lower cost PEFCs. In this study, we analyzed the transport properties of oxygen molecules in the CLs of PEFCs using the Monte Carlo (MC) method. The effect of oxygen scattering on the overall oxygen transport properties was investigated by considering the behavior on the surface of the ionomer film (surface diffusion) into the MC method, which simulates the overall transport in the PEFC CL. The objective of this study is to reproduce accurate oxygen transport by comparing the results of MC and molecular dynamics (MD) methods. First, we used the MC method to analyze oxygen scattering phenomena. In this study, we used the 3D structure data of CL in the MC simulations. The three-dimensional structure of the sample was reconstructed from sequential slice images. Molecules were assumed to reflect specularly on the boundaries of the simulation domain. Oxygen molecules were randomly placed in the simulation system. The time step was set at 5 ps and the simulation time was set at 4 μs. In order to examine the effect of surface diffusion on the transport properties of oxygen molecules, the simulation was performed using various conditions of surface diffusion. We calculated the effective diffusion coefficient of oxygen in the CL as the transport property of oxygen molecules in the MC method. As the surface diffusion coefficient increases, the effective diffusion coefficient of oxygen increases. When the surface diffusion coefficient is small, the effective diffusion coefficient of oxygen increases due to a decrease in the time constant, which determines the probability distribution of the surface residence time. However, when the surface diffusion coefficient is large, a different trend emerges. As the time constant increases, the effective diffusion coefficient has a peak value and then decreases. Next, to verify the model of surface diffusion in the MC method, we analyzed the scattering phenomenon of oxygen molecules in a simulation system that simulates the pores in the CL using the MD method. We modeled the nano pores in the CL as a slit between the ionomer walls in the MD method. Nafion with the equivalent weight (EW) of 1146 was used as polymer model. The number of Nafion chains is set at 4, and the water content λ is set at 7. Three-dimensional periodic boundary conditions were applied to the simulation domain. After the system was equilibrated, 1 ns of NVT simulation was performed for production. The temperature was set at 297 K. The behavior of oxygen molecules impacting on the ionomer wall was analyzed. We analyzed the behavior of oxygen molecules colliding with the ionomer membrane using the MD method. The average residence time of surface diffusion on the ionomer thin film was of the order of 10-10s. When the calculation results were compared with the MC results, it was found that the average residence time obtained by the MD method was the value where the surface diffusion coefficient affects much on the effective diffusion coefficient. Comparing the results of the MD method with the surface diffusion model used in the MC method, there are some discrepancies between the results and the model. For example, the MC method used a model in which oxygen molecules reflect diffusively on the ionomer surface. However, in the MD method, it was found that oxygen molecules tend to reflect in the direction of travel (Fig. 1). Therefore, a more accurate model of the MC method needs to be developed in the future. Figure 1

Process variations have become a critical issue in performance verification of high-performance designs. We present a new, statistical timing analysis method that accounts for inter- and intra-die process variations and their spatial correlations. Since statistical timing analysis has an exponential run time complexity, we propose a method whereby a statistical bound on the probability distribution function of the exact circuit delay is computed with linear run time. First, we develop a model for representing inter- and intra-die variations and their spatial correlations. Using this model, we then show how gate delays and arrival times can be represented as a sum of components, such that the correlation information between arrival times and gate delays is preserved. We then show how arrival times are propagated and merged in the circuit to obtain an arrival time distribution that is an upper bound on the distribution of the exact circuit delay. We prove the correctness of the bound and also show how the bound can be improved by propagating multiple arrival times. The proposed algorithms were implemented and tested on a set of benchmark circuits under several process variation scenarios. The results were compared with Monte Carlo simulation and show an accuracy of 3.32% on average over all test cases.

Abstract—Variations in the vertical electric field and atmospheric current in the near-surface atmosphere, accompanying strong earthquakes, are analyzed. The analysis is based on the data of the Center for Geophysical Monitoring in Moscow (CGM) and Geophysical observatory “Mikhnevo” of the Sadovsky Institute of Geosphere Dynamics of Russian Academy of Sciences (IDG RAS). We considered seismic events that occurred when the electric field and atmospheric current were not disturbed by anthropogenic sources and natural impacts unrelated to earthquakes. It is noted that the earthquakes are accompanied by the increased local variations in the electric field in the period of arrival of seismic waves at the observation point and variations associated with the source region of the seismic event. In the latter case, the effect appears as a bay-like decrease and increase and as alternating variations in the vertical gradient of the electric potential. Simultaneously, the earthquakes are accompanied by the increased variations in the atmospheric current. For the first time it is shown that the main shock is accompanied by the increased variations in the electrical characteristics of the near-surface atmosphere at significant distances from the seismic source.

Gold nanoparticle decorated graphene for efficient sensing of NO2 gas

Temperature dependence of characteristic parameters of the Au/SnO 2/ n-Si (MIS) Schottky diodes

Mechanical and thermal reliability of printed organic thin-film transistor

The variations in the electrical and mechanical properties of solution-processed amorphous indium–gallium–zinc–oxide thin-film transistors exposed to high-humidity ambient conditions for long periods were analyzed. When the TFT was exposed to high-humidity conditions, field-effect mobility severely decreased, while ON/OFF current ratio improved and subthreshold slope value remained nearly constant, which is different from that exposed to low-humidity condition. We found that the H2O molecules induce mechanical peeling of the active layer such that they act as acceptor-like deep states, which is very different from the prior results under low humidity condition. The variations in electrical characteristics were systematically analyzed using a technology-CAD simulation before and after exposure to highhumidity conditions.