Compact 2D modeling and drain current performance analysis of a work function engineered double gate tunnel field effect transistor

被引:0
|
作者
Saheli Sarkhel
Navjeet Bagga
Subir Kumar Sarkar
机构
[1] Jadavpur University,Department of Electronics and Telecommunication Engineering
来源
Journal of Computational Electronics | 2016年 / 15卷
关键词
Double gate (DG); Tunnel field effect transistor (TFET); Band-to-band tunneling (BTBT); Work function engineered gate (WFEG); Poisson’s equation;
D O I
暂无
中图分类号
学科分类号
摘要
The ongoing trend of device dimension miniaturization is attributed to a large extent by the development of several non-conventional device structures among which tunneling field effect transistors (TFETs) have attracted significant research attention due to its inherent characteristics of carrier conduction by built-in tunneling mechanism which in turn mitigates various short channel effects (SCEs). In this work, we have, incorporated the innovative concept of work function engineering by continuously varying the mole fraction in a binary metal alloy gate electrode along the horizontal direction into a double gate tunneling field effect transistor (DG TFET), thereby presenting a new device structure, a work function engineered double gate tunneling field effect transistor (WFEDG TFET). We have presented an explicit analytical surface potential modeling of the proposed WFEDG TFET by the solving the 2-D Poisson’s equation. From the surface potential expression, the electric field has been derived which has been utilized to formulate the expression of drain current by performing rigorous integration on the band-to-band tunneling generation rate over the tunneling region. Based on this analytical modeling, an overall performance comparison of our proposed WFEDG TFET with its normal DG TFET counterpart has been presented in this work to establish the superiority of our proposed structure in terms of surface potential and drain current characteristics. Analytical results have been compared with SILVACO ATLAS device simulator results to validate our present model.
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页码:104 / 114
页数:10
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