Session: 13-03-01: Computational Studies on MEMS and Nanostructures

Paper Number: 145663

145663 - Multiphysics Modeling and Simulation of Gas Sensor for No2 Detection 

In recent years, scientists have increasingly focused on environmental pollution, particularly its contribution to global warming, with a notable concern being the release of harmful gases like Nitrogen Dioxide (NO₂) from incomplete combustion in automobiles and industrial areas. Various methods, ranging from sophisticated lab equipment to portable gas chromatography systems, have been developed to detect NO₂ levels. Among these, Metal-Oxide Semiconductor (MOS) gas sensors have gained attention for their high sensitivity, selectivity, low power consumption, simplicity, and cost-effectiveness.

Improving the performance of MOS sensors involves incorporating additives and catalysts to enhance selectivity, sensitivity, and reduce operating temperatures, crucial for lowering power consumption and optimizing reaction kinetics. Nano-sizing MOS and catalyst particles increases surface area, providing more reaction sites. Tin oxide (SnO₂), a widely studied n-type MOS material, has been extensively investigated in various forms with different catalysts and dopants for gas detection. Graphene and its derivatives (graphene oxide and reduced graphene oxide) have also emerged as promising catalysts within SnO₂ phases, facilitating gas reactions by enhancing adsorption/desorption processes. Graphene's high carrier mobility enables sensitivity to low NO₂ concentrations.

However, a challenge in SnO₂/graphene-based NO₂ sensors is the high operating temperature. Reduced graphene oxide (rGO), with high electron mobility at room temperature, has been explored as a sensing material to detect NO₂ at lower temperatures, owing to its enhanced adsorption/desorption properties on carbon sites, particularly due to the n-SnO₂/p-rGO heterojunction formed in composite materials. Other challenges in the fabrication of a novel MOS/rGO nanocomposite gas sensor include time constraints, budget limitations, and the need for a comprehensive understanding of sensing mechanisms and outcomes resulting from interaction with the target gas. To mitigate these challenges, one approach is to predict the sensor's sensing behavior prior to fabrication, thereby reducing costs associated with trial-and-error experimentation.

Hence, in this study a finite element (FE) model is developed in COMSOL Multiphysics software to simulate the sensing mechanism and the sensor performance of a SnO2/rGO gas sensor for the detection of NO₂ gas. The sensor design is based on experimental work and the results of the FE simulation work are compared with the experimental results for the validation of the sensor model. Various modules such as the laminar flow module, electric current module, heat transfer module and the transport of electric species module have been used in COMSOL for this analysis. This comprehensive approach ensures a thorough understanding of the sensor behavior and validates its performance for reliable gas detection applications.

Presenting Author: Parth Bansal University of Illinois at Urbana-Champaign

Presenting Author Biography: Parth Bansal is a graduate student at the University of Illinois.

Authors:

Parth Bansal University of Illinois at Urbana-Champaign
Yuan Jiang University of Illinois at Urbana-Champaign
Zhou Li Stanford University
Sergio Cordero Stanford University
Zahra Heussen Stanford University
Debbie Senesky Stanford University
Pingfeng Wang University of Illinois at Urbana-Champaign
Yumeng Li University of Illinois at Urbana-Champaign