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4 articles for “Electrostatic gating”
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A Comparative Analysis of Graphene Based Terahertz Reconfigurable Antennas: A Review
Abstract: In this paper, an overview of various reconfigurable antenna designs based on graphene material utilized for terahertz applications is presented. Terahertz electromagnetic spectrum is the term used to describe the frequency range between 0.1 and 10 THz. A promising material for THz reconfigurable antennas, graphene has a low skin effect and a built-in ability to tune by chemical or electrostatic gating. This study reviews the development of reconfigurable antenna for …
Published in Journal of Polymer & Composites · Vol. 11, Issue 5, 2023 · pp. 44–55 Read article
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High Performance Multi-Valued Logic (MVL)Gate Design Using FinFET
Abstract: CMOS scaling faces challenges such as leakage, power dissipation, and short channel effects. Multi-Valued Logic (MVL) offers higher information density and reduced interconnections. This work presents a FinFET-based MVL gate design that improves electrostatic control, switching speed, and reliability. Simulation results confirm reduced leakage power and enhanced performance compared to conventional logic. The proposed architecture demonstrates scalability for advanced technology nodes. It also shows potential for low-power applications in portable …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 34–45 Read article
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An Overview on MOSFET based Sensor Design
Abstract: In the past two decades the MOSFET has transformed from a simple switch in digital logic to an analog powerhouse that can be cofabricated with the sensing material on a single chip. MetalOxideSemiconductor FieldEffect Transistors (MOSFETs) have silently become the beating heart of modern sensor platforms, translating the faint whispers of physical, chemical, and biological phenomena into robust electrical signatures. This abstract surveys the latest advances that have turned the …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 20–26 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article