4.6 Article

A Parameter Extraction Methodology for Graphene Field-Effect Transistors

Journal

IEEE TRANSACTIONS ON ELECTRON DEVICES
Volume 70, Issue 3, Pages 1393-1400

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TED.2023.3239331

Keywords

Resistance; Logic gates; Parameter extraction; Semiconductor device modeling; Degradation; Quantum capacitance; MOSFET; Charge-carrier mobility; graphene field-effect transistors (GFETs); mobility degradation; model parameter extraction; series; contact resistance

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Graphene field-effect transistors (GFETs) have been used extensively for device characterization, and recently the focus has shifted to the methods for device characterization themselves. This article presents a structured methodology for extracting and validating GFET model parameter values based on the physics of FETs and GFETs. The extraction process divides the GFET resistance into a constant part believed to represent the series/contact resistance and a gate-voltage-dependent part that contains first-order information about mobility degradation. The main influence of quantum capacitance can be captured by an equivalent oxide thickness (EOT) instead of the insulator thickness.
Graphene field-effect transistors (GFETs) have now been around for more than a decade and their transfer characteristics extensively used for device characterization. Model parameters, such as low-field charge-carrier mobility and device contact/series resistance, have often been the main interest. However, not until recently have the methods for device characterization themselves been the focus of research publications. In this article, I report on a structured methodology for extracting and validating the extracted GFET model parameter values based on the physics of FETs in general and of GFETs in particular. During the extraction process, the GFET resistance is divided into two parts, a constant part and a gate-voltage-dependent part, where the constant part often has been believed to represent the series/contact resistance. However, part of it depends on the channel length and contains first-order information about mobility degradation. Finally, I show that the main influence of the quantum capacitance can be captured by an equivalent oxide thickness (EOT) replacing the insulator thickness.

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