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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Abstract
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 |
| Statistic Details: | View Download Statistic |
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