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- Title
Optimization of tunneling current in ferroelectric tunnel FET using genetic algorithm.
- Authors
Guenifi, Naima; Rahi, Shiromani Balmukund; Benmahdi, Faiza; Chabane, Houda
- Abstract
Tunnel field effect transistor (TFET) is a gate-controlled, quantum FET device, exhibiting band-to-band tunneling (BTBT) transport phenomena with lower subthreshold swing (SS) than bulk MOSFET devices. Low ON-state current (ION) is an inherent problem with TFET devices. Various research groups are working to address the limitations due to low ON-state current and for performance improvement of the device. The work in this paper is an attempt to overcome the low switching current issue by using ferroelectric material (Fe), barium titanate (BaTiO3) in conventional double gate TFET, having Si1-xGex/Si semiconductors configuration. In the proposed TFET device, the high-κ dielectric HfO2 is replaced by BaTiO3, ferroelectric material (Fe) in the source region. The replacement of HfO2 gate materials by BaTiO3 Fe is found to improve ION (~ order of 10−8 A/µm -to-10−5 A/µm). The FeDGTFET device shows ~ 103 times improvement in ION with unaffected IOFF (~ 10−20 A/µm). In circuit and system design figure of merit, optimization is a critical task for designers. The work in this paper is divided into three sections. Initially, two structures based on high-κ, one with only high-κ (HfO2) DGTFET and the other one based on HfO2 and ferroelectric material BaTiO3 (FeDGTFET), are compared. Analysis of the electric parameters of the two structures shows the performance advantage of the structure based on the ferroelectric material. Next, a parametric study of the FeDGTFET structure is performed linking Silvaco Atlas with MATLAB to analyze the electrical parameters of FeDGTFET. Finally, an optimization technique called algorithm genetic 'AG' is employed to show enhancement in the ION current from 10−5 to 10−4A/µm without affecting the IOFF.
- Subjects
TUNNEL field-effect transistors; GENETIC algorithms; FIELD-effect transistors; FERROELECTRIC materials; TUNNEL junctions (Materials science); BARIUM titanate
- Publication
Journal of Supercomputing, 2023, Vol 79, Issue 14, p15773
- ISSN
0920-8542
- Publication type
Article
- DOI
10.1007/s11227-023-05240-0