Kinetic Model for H2S Adsorption on NiO Surface in Resistive MEMS Gas Sensors: Coupling Mass Transfer, Multisite Adsorption, and Surface Interactions

Abstract

Heterogeneous processes at gas--solid interfaces in resistive gas sensors involve external diffusion, multisite adsorption, surface migration and desorption, often complicated by site heterogeneity and lateral interactions. In this work, we develop a non-equilibrium kinetic framework that explicitly couples external mass transfer to multisite Langmuir--Hinshelwood adsorption–desorption with lateral adsorbate interactions and surface diffusion. The model is constructed to factorise material-specific (NiO site types and morphology), analyte-specific (molecular versus dissociative H$_2$S adsorption and concentration-dependent desorption) and transport-specific (MEMS-based gas delivery and mass-transfer limitations) contributions, which enables transfer of kinetic parameters across different sensing layers, morphologies and analytes. Validation on a MEMS-based NiO sensor for H$_2$S demonstrates that only a model including dissociative adsorption, chemisorption with long-lived sulfur-containing species and concentration-dependent desorption can reproduce the experimentally observed multistage transients and apparent relaxation times. By linking surface coverage dynamics directly to conductivity via a morphology-dependent power-law relation, the framework bridges microscopic surface chemistry and macroscopic sensor signal, providing a physically grounded alternative to phenomenological relaxation models and a tool for generating synthetic training data for electronic-nose applications.

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Article information

Article type
Paper
Submitted
02 Dec 2025
Accepted
09 Feb 2026
First published
17 Feb 2026

Phys. Chem. Chem. Phys., 2026, Accepted Manuscript

Kinetic Model for H2S Adsorption on NiO Surface in Resistive MEMS Gas Sensors: Coupling Mass Transfer, Multisite Adsorption, and Surface Interactions

A. Kondrateva, I. Goltaev and M. Mishin, Phys. Chem. Chem. Phys., 2026, Accepted Manuscript , DOI: 10.1039/D5CP04688B

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