Optimal Design Of Junctionless Double Gate Vertical MOSFET Using Hybrid Taguchi-GRA With ANN Prediction

Salehuddin, Fauziyah and Kaharudin, Khairil Ezwan and Roslan, Ameer Farhan and Mohd Zain, Anis Suhaila (2019) Optimal Design Of Junctionless Double Gate Vertical MOSFET Using Hybrid Taguchi-GRA With ANN Prediction. Journal of Mechanical Engineering and Sciences, 13 (3). pp. 5455-5479. ISSN 2289-4659

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Random parameter variations have been an influential factor that deciding the performance of a metal-oxide-semiconductor field effect transistor (MOSFET), especially in nano-scale regime. Thus, controlling the variation of those parameters becomes extremely crucial in order to attain an acceptable performance of an ultra-small MOSFET. This paper proposes an approach to optimally design a n-type junctionless double-gate vertical MOSFET (nJLDGVM) via hybrid Taguchi-grey relational analysis (GRA) with artificial neural networks (ANN) prediction. The device is designed using a combination of 2-D simulation tools (Silvaco) and hybrid Taguchi-GRA with a well-trained ANN prediction. The investigated device parameters consist of channel length (Lch), pillar thickness (Tp), channel doping (Nch) and source/drain doping (Nsd). The optimized design parameters of the device demonstrate a tolerable magnitude of on-state current (ION), off-state current (IOFF), on-off ratio, transconductance (gm), cut-off frequency (fT) and maximum oscillation frequency (fmax), measured at 2344.9 µA/µm, 2.53 pA/µm, 927 x 106, 4.78 mS/µm, 121.5 GHz and 2469 GHz respectively.

Item Type: Article
Uncontrolled Keywords: Channel doping, channel length, pillar thickness, source/drain doping, Double Gate Vertical MOSFET, Hybrid Taguchi-GRA
Divisions: Faculty of Electronics and Computer Engineering > Department of Computer Engineering
Depositing User: Norfaradilla Idayu Ab. Ghafar
Date Deposited: 21 Oct 2020 08:32
Last Modified: 21 Oct 2020 08:32
URI: http://eprints.utem.edu.my/id/eprint/24268
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