Statistical Modelling of ft to Process Parameters in 30 nm Gate Length Finfets

TL;DR

This paper models the impact of process variations on the unity gain frequency (ft) in 30 nm FinFETs using extensive simulations and statistical analysis, identifying key sensitive parameters affecting device performance.

Contribution

It introduces a statistical model for ft in 30 nm FinFETs based on sensitivity analysis and validates it with experimental simulation data.

Findings

ft is highly sensitive to gate length, underlap, and doping variations.

The statistical model accurately predicts ft across different process variations.

Certain parameters like source/drain width and work function have less impact on ft.

Abstract

This paper investigates the effect of process variations on unity gain frequency (ft) in 30 nm gate length FinFET by performing extensive TCAD simulations. Six different geometrical parameters, channel doping, source/drain doping and gate electrode work function are studied for their sensitivity on ft. It is found that ft is more sensitive to gate length, underlap, gate-oxide thickness, channel and Source/Drain doping and less sensitive to source/drain width and length, and work function variations. Statistical modelling has been performed for ft through design of experiment with respect to sensitive parameters. The model has been validated through a comparison between random set of experimental data simulations and predicted values obtained from the model.