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Subthreshold Analytical Model of Asymmetric Gate Stack Triple Metal Gate all Around MOSFET (AGSTMGAAFET) for Improved Analog Applications
Subthreshold Analytical Model of Asymmetric Gate Stack Triple Metal Gate all Around MOSFET (AGSTMGAAFET) for Improved Analog Applications
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Subthreshold Analytical Model of Asymmetric Gate Stack Triple Metal Gate all Around MOSFET (AGSTMGAAFET) for Improved Analog Applications
Subthreshold Analytical Model of Asymmetric Gate Stack Triple Metal Gate all Around MOSFET (AGSTMGAAFET) for Improved Analog Applications

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Subthreshold Analytical Model of Asymmetric Gate Stack Triple Metal Gate all Around MOSFET (AGSTMGAAFET) for Improved Analog Applications
Subthreshold Analytical Model of Asymmetric Gate Stack Triple Metal Gate all Around MOSFET (AGSTMGAAFET) for Improved Analog Applications
Journal Article

Subthreshold Analytical Model of Asymmetric Gate Stack Triple Metal Gate all Around MOSFET (AGSTMGAAFET) for Improved Analog Applications

2022
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Overview
In this paper, we have proposed a 2D analytical model for Asymmetric gate stack triple metal gate MOSFET(AGSTMGAAFET) and performed a comparative analysis with the simulation results obtained using the SILVACO 3D simulation software. Existing devices such as gate all around single metal (SMGAAFET), gate all around triple metal (TMGAAFET), gate stack single metal (GSSMGAAFET), gate stack triple metal (GSTMGAAFET) and asymmetric gate stack single metal (AGSTMGAAFET) have been compared with our proposed structure AGSTMGAAFET. Our device provides excellent performance in terms of drain current, transconductance, output conductance, current gain, maximum transducer power gain which shows our device’s suitability for various analog applications moreover the potential and electric field plots obtained have twostep profile and extremely low electric field near the drain region which ordains our device with the ability to suppress various SCE’s like DIBL and hot-carrier effect. The analytical model and simulation results show good convergence in values which validate the correctness of the proposed model.