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This document provides some references on the Diversity, Equity, and Inclusion in CAS (DEICAS) event at the 2023 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS 2023). [ABSTRACT FROM AUTHOR]

This work presents multivariate regression polynomial as a versatile and efficient method for DC modeling of modern transistors with very different underlying physics including MOSFET (metal-oxide-semiconductor field-effect transistor), MESFET (metal–semiconductor field-effect transistor), HBT (heterojunction bipolar transistor), HEMT (High-electron-mobility transistor) and a novel silicon-on-insulator four-gate transistors (G4FET). A set of available data from analytic solution, TCAD simulation, and experimental measurements for different operating conditions is used to empirically determine the parameters of this model and a different set of test data is used to verify its predictive accuracy. The developed model expresses the drain current as a single multivariate regression polynomial with its validity spanning across different possible operating regions as long as the chosen independent variables lie within the range of training data set. The continuity of the resulting polynomial and its first and second order derivatives make it particularly suitable for implementation in a circuit simulator. The model also provides a method for further simplification based on prior knowledge of the underlying physical mechanism and shows excellent predictive capability for different kinds of devices. This can be very useful for modeling deep-submicron emerging devices for which any closed-form analytical solution is not yet available. [ABSTRACT FROM AUTHOR]

A macromodel of silicon-on-insulator (SOI) four-gate transistor (G4FET) is presented in this paper to aid circuit designers to explore innovative applications circuit with this multi-gate transistor. A number of works based on analytical solution, numerical simulation and experimental results of G4FET have been previously reported. However, designing new interesting circuits with G4FETs requires a SPICE model that will work sufficiently well throughout the desired operating regions. Although it is theoretically possible to solve coupled non-linear differential equations to explore different operating conditions, this will take an excessive amount of time making it unsuitable for useful circuit design. Therefore, a macromodel approach is adopted in this work to provide a reasonably fast and accurate circuit simulation. G4FET combines the functionality of MOSFET and JFET devices which already have robust, fast and reliable SPICE models. A macromodel approach which is capable of combining these existing models including the interactions between multiple gates will be beneficial for any circuit designer. The feasibility of the macromodel is justified by simulating several analog and digital circuits and comparing against available experimental results. [ABSTRACT FROM AUTHOR]

In this study, we have investigated the thermal transport characteristics of single-layer tungsten disulfide, WS 2 nanoribbons (SLTDSNRs) using equilibrium molecular dynamics simulations with the help of Green-Kubo formulation. Using Stillinger-Weber (SW) inter-atomic potential, the calculated room temperature thermal conductivities of 15 nm × 4 nm pristine zigzag and armchair SLTDSNRs are 126 ± 10 W m -1 K -1 and 110 ± 6 W m -1 K -1 , respectively. We have explored the dependency of thermal conductivity on temperature, width, and length of the nanoribbon. The study shows that the thermal conductivity of the nanoribbon decreases with the increase in temperature, whereas the thermal conductivity increases with an increase in either the width or length of the ribbon. The thermal conductivity does not increase uniformly as the size of the ribbon changes. We have also observed that the thermal conductivity of SLTDSNRs depends on edge orientations; the zigzag nanoribbon has greater thermal conductivity than the armchair nanoribbon, regardless of temperature or dimension variations. Our study additionally delves into the tunable thermal properties of SLTDSNRs by incorporating defects, namely vacancies such as point vacancy, edge vacancy, and bi-vacancy. The thermal conductivities of nanoribbons with defects have been found to be considerably lower than their pristine counterparts, which aid in enhanced values for the thermoelectric figure of merit (zT). We have varied the vacancy concentration within a range of 0.1% to 0.9% and found that a point vacancy concentration of 0.1% leads to a 64% reduction in the thermal conductivity of SLTDSNRs. To elucidate these phenomena, we have calculated the phonon density of states for WS 2 under different aspects. The findings of our work provide important understandings of the prospective applications of WS 2 in nanoelectronic and thermoelectric devices by tailoring the thermal transport properties of WS 2 nanoribbons., (© 2024 IOP Publishing Ltd.)