Optimal Design Of Junctionless Double Gate Vertical MOSFET Using Hybrid Taguchi-GRA With ANN Prediction
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 p...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit UMP
2019
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| Online Access: | http://eprints.utem.edu.my/id/eprint/24268/2/KEKAHARUDIN-JMES-SEPT2019.PDF http://eprints.utem.edu.my/id/eprint/24268/ https://journal.ump.edu.my/jmes/article/view/441/476 https://doi.org/10.15282/jmes.13.3.2019.16.0442 |
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| Summary: | 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. |
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