A statistical thermodynamics model for monolayer gas adsorption on graphene-based materials: implications for gas sensing applications

Abstract

Field-effect transistor-based conductance gas sensors are attracting considerable research interest because of their miniaturized size, high sensitivity, and portability. Here, we propose statistical thermodynamics models to analytically characterize monolayer gas molecule adsorption on crystalline and amorphous solid surfaces in terms of adsorption density and coverage, respectively, which are critical for gas sensing applications. By testing the monolayer adsorption of gas molecules, such as CO, NO, NH₃ and NO₂, on graphene and reduced graphene oxide (rGO), we found that adsorption density and coverage can be estimated from only the binding energy of gas molecules with a high accuracy compared with the exact values obtained by solving the Schrödinger equation. Moreover, the experimentally observed (e.g., NO₂) density on graphene is close to our theoretical prediction. The proposed approaches to quantitatively characterize gas adsorption on solid surfaces are of great significance to help understand and optimize the performance of gas sensors.