Intelligent Modeling of Electrical Characteristics of Multi-Channel Gate All Around Silicon Nanosheet MOSFETs Induced by Work Function Fluctuation

Chandni Akbar, Yiming Li*, Wen Li Sung

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Intelligent model (IM) of device and performance prediction is an emerging methodology in the IC industry. This paper for the first time presents an optimized intelligent model approach based on an artificial neural network (ANN) to study the effects of a crucial source of variation, i.e., work function fluctuation (WKF) of multi-channel (MC) gate-all-around (GAA) silicon (Si) nanosheet (NS) MOSFET. Various fluctuated devices are simulated and their ID-VG curves, as well as their extracted electrical properties, are investigated using IM based ANN algorithm. These predicted electrical properties are estimated accurately and show that on-current (ION) is decreased from top contacts to the bottom source/drain contact as the electrostatic potential (V) is decreasing in MC GAA Si NS MOSFET. IM-based ANN methodology has negligible computational cost as compared to 3D device simulation. Therefore, this intelligent modeling approach can be utilized to accelerate the device simulation for advanced semiconductor nano-devices.

Original languageEnglish
Title of host publication2022 IEEE 22nd International Conference on Nanotechnology, NANO 2022
PublisherIEEE Computer Society
Pages261-264
Number of pages4
ISBN (Electronic)9781665452250
DOIs
StatePublished - 2022
Event22nd IEEE International Conference on Nanotechnology, NANO 2022 - Palma de Mallorca, Spain
Duration: 4 Jul 20228 Jul 2022

Publication series

NameProceedings of the IEEE Conference on Nanotechnology
Volume2022-July
ISSN (Print)1944-9399
ISSN (Electronic)1944-9380

Conference

Conference22nd IEEE International Conference on Nanotechnology, NANO 2022
Country/TerritorySpain
CityPalma de Mallorca
Period4/07/228/07/22

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