ArticleScientific reports2021
Simulation of gas sensing mechanism of porous metal oxide semiconductor sensor based on finite element analysis.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
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- Transparent Al-Doped ZnO Thin Films for High-Sensitivity NOSensors (Basel, Switzerland) · 2025Article
- Synergistic integration of plasmonic and perovskite nanosurfaces to create a multi-gas sensor for environmental monitoring.RSC advances · 2024Article
- Study on the Simulation of Biosensors Based on Stacked Source Trench Gate TFET.Nanomaterials (Basel, Switzerland) · 2023Article
- A Statistical Analysis of Response and Recovery Times: The Case of Ethanol Chemiresistors Based on Pure SnOSensors (Basel, Switzerland) · 2022Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, finite element analysis is increasingly adopted to simulate the mechanism of metal oxide semiconductor (MOS) resistive gas sensors. In this article, the chemical reaction engineering module in the COMSOL Multiphysics tool is used to describe the dynamic equilibrium process of oxygen ions in the sensor. The boundary conditions of temperature transfer, conductivity model, and mass transfer are applied to simulate the convection, diffusion, and penetration processes. The response of the sensor at different temperatures (445 K-521 K) and different target gas concentrations (1-500 ppm) is simulated. In this paper, the dynamic model of oxygen ions is used creatively as a bridge between gas concentration and sensor response instead of the traditional direct parameter fitting method. The simulated result of the surface oxygen ion control and permeability control model of the MOS gas sensor shows a good agreement with the real sensor. For explaining the principle of metal oxide semiconductor gas sensors simulations has been performed on COMSOL Multiphysics software. The proposed method in this paper is based on the underlying transfer logic of the sensor signal, it is expected to predict the sensor signal and assist the sensor design.
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Registered trials
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