Work

Quantitative modeling of the non-monotonic sensitivity of defect-engineered graphene sensors

Year: 2025

Type: article

Abstract: Defect engineering has been explored as a means to improve the performance of graphene-based gas sensors. However, sensor sensitivity often exhibits a non-monotonic relationship with defect density, presenting challenges for device optimization. In this study, we introduce a quantitative physical model aimed at describing and anticipating this behavior. Graphene samples were irradiated with deuteron ions to generate a controlled range of defect densities, which were characterized using Raman spectroscopy. Sensitivity to hydrogen showed a Λ-shaped dependence on defect density, with a peak response observed at an intermediate concentration. This behavior is attributed to the competing effects of signal enhancement and structural degradation induced by defects. The proposed model expresses sensitivity as a function of two experimentally derived parameters an activation coefficient ( C n ) and a degradation coefficient ( γ n ), providing insight into the underlying sensing mechanism.

Source: Scientific Reports

DOI: 10.1038/s41598-025-27734-y

Authors: Sunmog Yeo, Junhyeok Seo, Young Jun Yoon, Kibeom Kim

Institutions: Korea Atomic Energy Research Institute, Gyeongkuk National University, Soonchunhyang University

Language: English

Topic: Gas Sensing Nanomaterials and Sensors

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,690

Funder: Korea Atomic Energy Research Institute