Impact of Device Resistances in the Performance of Graphene-based Terahertz Photodetectors

TL;DR

This paper investigates how internal device resistances affect the performance of graphene-based Terahertz photodetectors, demonstrating that reducing resistance improves responsivity and noise performance, with implications for optimizing future THz detection technologies.

Contribution

It provides a detailed analysis of internal resistances in dual-gate GFETs and shows how tuning these resistances enhances photodetector performance, supported by experimental and theoretical agreement.

Findings

Reducing internal resistance improves responsivity.

Dual-gate architecture allows significant resistance tuning.

Series resistance model accurately explains device behavior.

Abstract

In recent years, graphene Field-Effect-Transistors (GFETs) have demonstrated an outstanding potential for Terahertz (THz) photodetection due to their fast response and high-sensitivity. Such features are essential to enable emerging THz applications, including 6G wireless communications, quantum information, bioimaging and security. However, the overall performance of these photodetectors may be utterly compromised by the impact of internal resistances presented in the device, so-called access or parasitic resistances. In this work, we provide a detailed study of the influence of internal device resistances in the photoresponse of high-mobility dual-gate GFET detectors. Such dual-gate architectures allow us to fine tune (decrease) the internal resistance of the device by an order of magnitude and consequently demonstrate an improved responsivity and noise-equivalent-power values of the photodetector, respectively. Our results can be well understood by a series resistance model, as shown by the excellent agreement found between the experimental data and theoretical calculations. These findings are therefore relevant to understand and improve the overall performance of existing high-mobility graphene photodetectors.