Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm

As the technology nodes of semiconductor devices have become finer and more complex, progressive scaling down has been implemented to achieve higher densities for electronic devices. Thus, three-dimensional (3D) channel field-effect transistors (FETs), such as fin-shaped FETs (FinFETs) and gate-all-...

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Autores principales:	Chuntaek Park, Ilgu Yun
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	GAAFETs self-heating effect leakage current thermal time constant neural network modeling genetic algorithm Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/a6d62d0d609f47049321d30185101205
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spelling	oai:doaj.org-article:a6d62d0d609f47049321d301851012052021-11-11T15:36:38ZOptimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm10.3390/electronics102125702079-9292https://doaj.org/article/a6d62d0d609f47049321d301851012052021-10-01T00:00:00Zhttps://www.mdpi.com/2079-9292/10/21/2570https://doaj.org/toc/2079-9292As the technology nodes of semiconductor devices have become finer and more complex, progressive scaling down has been implemented to achieve higher densities for electronic devices. Thus, three-dimensional (3D) channel field-effect transistors (FETs), such as fin-shaped FETs (FinFETs) and gate-all-around FETs (GAAFETs), have become popular as they have increased effective surface areas for the channels (<i>W<sub>eff</sub></i>), owing to the scaling down strategy. These 3D channel FETs, which have completely covered channel structures with gate oxide and metal, are prone to the self-heating effect (SHE). The SHE is generally known to degrade the on-state drain current; however, when AC pulsed inputs are applied to these devices, the SHE also degrades the off-state leakage current during the off-phase of the pulse. In this study, an optimization methodology to minimize leakage current generation by the SHE is examined.Chuntaek ParkIlgu YunMDPI AGarticleGAAFETsself-heating effectleakage currentthermal time constantneural network modelinggenetic algorithmElectronicsTK7800-8360ENElectronics, Vol 10, Iss 2570, p 2570 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	GAAFETs self-heating effect leakage current thermal time constant neural network modeling genetic algorithm Electronics TK7800-8360
spellingShingle	GAAFETs self-heating effect leakage current thermal time constant neural network modeling genetic algorithm Electronics TK7800-8360 Chuntaek Park Ilgu Yun Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm
description	As the technology nodes of semiconductor devices have become finer and more complex, progressive scaling down has been implemented to achieve higher densities for electronic devices. Thus, three-dimensional (3D) channel field-effect transistors (FETs), such as fin-shaped FETs (FinFETs) and gate-all-around FETs (GAAFETs), have become popular as they have increased effective surface areas for the channels (<i>W<sub>eff</sub></i>), owing to the scaling down strategy. These 3D channel FETs, which have completely covered channel structures with gate oxide and metal, are prone to the self-heating effect (SHE). The SHE is generally known to degrade the on-state drain current; however, when AC pulsed inputs are applied to these devices, the SHE also degrades the off-state leakage current during the off-phase of the pulse. In this study, an optimization methodology to minimize leakage current generation by the SHE is examined.
format	article
author	Chuntaek Park Ilgu Yun
author_facet	Chuntaek Park Ilgu Yun
author_sort	Chuntaek Park
title	Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm
title_short	Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm
title_full	Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm
title_fullStr	Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm
title_full_unstemmed	Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm
title_sort	optimization of self-heating driven leakage current properties of gate-all-around field-effect transistors using neural network modeling and genetic algorithm
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a6d62d0d609f47049321d30185101205
work_keys_str_mv	AT chuntaekpark optimizationofselfheatingdrivenleakagecurrentpropertiesofgateallaroundfieldeffecttransistorsusingneuralnetworkmodelingandgeneticalgorithm AT ilguyun optimizationofselfheatingdrivenleakagecurrentpropertiesofgateallaroundfieldeffecttransistorsusingneuralnetworkmodelingandgeneticalgorithm
_version_	1718435070291738624

Optimization of Self-Heating Driven Leakage Current Properties of Gate-All-Around Field-Effect Transistors Using Neural Network Modeling and Genetic Algorithm

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