Physics-Based Compact Modeling for the Drain Current Variability in Single-Layer Graphene FETs

TL;DR

This paper introduces a physics-based compact model that accurately predicts drain current variability in monolayer graphene FETs, accounting for noise sources like mobility fluctuations, validated through experiments on multiple GFETs.

Contribution

It presents the first physics-based compact model for GFET drain current fluctuations, incorporating physical noise mechanisms and validated experimentally.

Findings

Model accurately predicts ID variability across bias conditions.

Physical noise mechanisms are confirmed as primary sources of fluctuations.

Model validated on multiple GFETs with different sizes and bias states.

Abstract

For the growth of emerging graphene field-effect transistor (GFET) technologies, a thorough characterization of on-wafer variability is required. Here, we report for the first time a physics-based compact model, which precisely describes the drain current (ID) fluctuations of monolayer GFETs. Physical mechanisms known to generate 1/f noise in transistors, such as carrier number and Coulomb scattering mobility fluctuations, are also revealed to cause ID variance. Such effects are considered in the model by being activated locally in the channel and the integration of their contributions from source to drain results in total variance. The proposed model is experimentally validated from a statistical population of three different-sized solution-gated (SG) GFETs from strong p- to strong n-type bias conditions. A series resistance ID variance model is also derived mainly contributing at high carrier densities.