Identification of Sarin Simulant DMMP Based on a Laminated MOS Sensor Using Article Swarm Optimization-Backpropagation Neural Network

A Pt@CeLaCoNiOx/Co@SnO<sub>2</sub> laminated MOS sensor was prepared using Co@SnO<sub>2</sub> as the gas-sensitive film material and Pt@CeLaCoNiOx as the catalytic film material. The sensor was verified to exhibit good sensing performances for dimethyl methylphosphonate, a simulant of Sarin, under a temperature modulation, and characteristic peaks appeared in the resistance response curves only for dimethyl methylphosphonate. The Article Swarm Optimization-Backpropagation Neural Network had a good ability to identify the resistance response data of dimethyl methylphosphonate. The identification accuracy increased as the concentration of dimethyl methylphosphonate increased. This scheme can effectively identify whether the test gas contained dimethyl methylphosphonate or not, which provided a reference for achieving the high selectivity of the MOS sensor for Sarin.

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Publication Details

Journal
Sensors
Published
2025-04-25
DOI
https://doi.org/10.3390/s25092734
Primary Topic
Gas Sensing Nanomaterials and Sensors
Type
article
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Identification of Sarin Simulant DMMP Based on a Laminated MOS Sensor Using Article Swarm Optimization-Backpropagation Neural Network

Yelin Qi, Gu Jin, Rui Yan, Yadong Liu et al.
Sensors
Gas Sensing Nanomaterials and Sensors
article

Identification of Sarin Simulant DMMP Based on a Laminated MOS Sensor Using Article Swarm Optimization-Backpropagation Neural Network

Yelin Qi, Gu Jin, Rui Yan, Yadong Liu, Shuya Cao, Ting Liang
article en

Abstract

A Pt@CeLaCoNiOx/Co@SnO<sub>2</sub> laminated MOS sensor was prepared using Co@SnO<sub>2</sub> as the gas-sensitive film material and Pt@CeLaCoNiOx as the catalytic film material. The sensor was verified to exhibit good sensing performances for dimethyl methylphosphonate, a simulant of Sarin, under a temperature modulation, and characteristic peaks appeared in the resistance response curves only for dimethyl methylphosphonate. The Article Swarm Optimization-Backpropagation Neural Network had a good ability to identify the resistance response data of dimethyl methylphosphonate. The identification accuracy increased as the concentration of dimethyl methylphosphonate increased. This scheme can effectively identify whether the test gas contained dimethyl methylphosphonate or not, which provided a reference for achieving the high selectivity of the MOS sensor for Sarin.

SensorsVol. 25(9)
Openalex Percentile: Top 93%
Gas Sensing Nanomaterials and Sensors
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Identification of Sarin Simulant DMMP Based on a Laminated MOS Sensor Using Article Swarm Optimization-Backpropagation Neural Network — Yelin Qi, Gu Jin, et al. · Sensors (2025) | TGRS Research Map | TGRS