Modeling Multigate Negative Capacitance Transistors With Self-Heating Effects

Jiao, Yanxin; Huang, Xiaoqing; Rong, Zhao; Ji, Zhigang; Wang, Runsheng; Zhang, Lining

doi:10.1109/ted.2022.3166853

Cited by 4 publications

(1 citation statement)

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“…gate-all-around FETs, Junction-less FETs, etc, and reported an admirable electrostatic performance [2][3][4][5][6]. NC-FinFET appeared as a prominent solution to the short channel effects (SCE); however, they are severely affected by reliability issues like self-heating effect [7,8], random dopant fluctuations (RDF) [9][10][11], work function fluctuations, etc [12,13]. In Fin-FETs, the thin fin width (t FIN ) hinders the substrate doping from altering the threshold voltage (V TH ) in the presence of RDF; thus, insisting on the need for a tunable gate work function [4].…”

Section: Introductionmentioning

confidence: 99%

Quasi-analytical model of surface potential and drain current for trigate negative capacitance FinFET: a superposition approach

Chauhan¹,

Samajdar²,

Bagga³

2022

Semicond. Sci. Technol.

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Negative Capacitance (NC) obtained from the ferroelectric (FE) polarization switching is a widely adopted approach for the realization of low power, high-performance devices. In this paper, for the first time, we have developed a 3D quasi-analytical model for the surface potential and drain current of the Trigate (TG) NC-FinFET using the superposition approach. Till date, only double gate uniformly doped NC-FinFET structures have been explored, which does not reveal the practicality of the device. Therefore, we perform an extensive device evaluation: 1) by solving the Poisson equation separately for the side gates (double gate) and the top gate to acquire a complete model for tri-gate FinFET using superposition principle; 2) to mimic the actual source/drain (S/D) doping, we included Gaussian doping in our proposed model; 3) with the incorporation of the laterally extended gate and S/D underlap. The model data are found in good agreement with the well-calibrated simulation data. We have taken the parabolic approximation method and appropriate boundary conditions to solve the Poisson equation.

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