Impact of randomly distributed dopants on Ω-gate junctionless silicon nanowire transistors

This paper presents experimental and simulation analysis of an Ω-shaped silicon junctionless nanowire field-effect transistor (JL-NWT) with gate lengths of 150 nm and diameter of the Si channel of 8 nm. Our experimental measurements reveal that the ON-currents up to 1.15 mA/μm for 1.0 V and 2.52 mA/μm for the 1.8-V gate overdrive with an OFF-current set at 100 nA/μm. Also, the experiment data reveal more than eight orders of magnitude ON-current to OFF-current ratios and an excellent subthreshold slope of 66 mV/dec recorded at room temperature. The obtained experimental current-voltage characteristics are used as a reference point to calibrate the simulations models used in this paper. Our simulation data show good agreement with the experimental results. All simulations are based on drift-diffusion formalism with activated density gradient quantum corrections. Once the simulations methodology is established, the simulations are calibrated to the experimental data. After this, we have performed statistical numerical experiments of a set of 500 different JL-NWTs. Each device has a unique random distribution of the discrete dopants within the silicon body. From those statistical simulations, we extracted important figures of merit, such as OFF-current and ON-current, subthreshold slope, and voltage threshold. The performed statistical analysis, on samples of those 500 JL-NWTs, shows that the mean ID-VGs characteristic is in excellent agreement with the experimental measurements. Moreover, the mean ID-VGs characteristic reproduces better the subthreshold slope data obtained from the experiment in comparison to the continuous model simulation. Finally, performance predictions for the JL transistor with shorter gate lengths and thinner oxide regions are carried out. Among the simulated JL transistors, the configuration with 25-nm gate length and 2-nm oxide thickness shows the most promising characteristics offering scalable designs

An Adaptable Foveating Vision Chip

Published versio

Neural-network dedicated processor for solving competitive assignment problems

A neural-network processor for solving first-order competitive assignment problems consists of a matrix of N x M processing units, each of which corresponds to the pairing of a first number of elements of (R sub i) with a second number of elements (C sub j), wherein limits of the first number are programmed in row control superneurons, and limits of the second number are programmed in column superneurons as MIN and MAX values. The cost (weight) W sub ij of the pairings is programmed separately into each PU. For each row and column of PU's, a dedicated constraint superneuron insures that the number of active neurons within the associated row or column fall within a specified range. Annealing is provided by gradually increasing the PU gain for each row and column or increasing positive feedback to each PU, the latter being effective to increase hysteresis of each PU or by combining both of these techniques

CMOS array design automation techniques

A low cost, quick turnaround technique for generating custom metal oxide semiconductor arrays using the standard cell approach was developed, implemented, tested and validated. Basic cell design topology and guidelines are defined based on an extensive analysis that includes circuit, layout, process, array topology and required performance considerations particularly high circuit speed

Self assembled three-dimensional nonvolatile memories

A promising strategy for for the realisation of three-dimensional memories could be the self assembly of articial sub-micron elements (smarticles). Such elements can be realised by combining edge-lithography techniques and anisotropic etching. The first experiments into this direction are encouraging

Energy challenges for ICT

The energy consumption from the expanding use of information and communications technology (ICT) is unsustainable with present drivers, and it will impact heavily on the future climate change. However, ICT devices have the potential to contribute signi - cantly to the reduction of CO2 emission and enhance resource e ciency in other sectors, e.g., transportation (through intelligent transportation and advanced driver assistance systems and self-driving vehicles), heating (through smart building control), and manu- facturing (through digital automation based on smart autonomous sensors). To address the energy sustainability of ICT and capture the full potential of ICT in resource e - ciency, a multidisciplinary ICT-energy community needs to be brought together cover- ing devices, microarchitectures, ultra large-scale integration (ULSI), high-performance computing (HPC), energy harvesting, energy storage, system design, embedded sys- tems, e cient electronics, static analysis, and computation. In this chapter, we introduce challenges and opportunities in this emerging eld and a common framework to strive towards energy-sustainable ICT