Identification of Gas Mixture with the MEMS Sensor Arrays by a Pattern Recognition

Bum Joon Kim, Jung Sik Kim

Research output: Contribution to journalArticlepeer-review

Abstract

Gas identification techniques using pattern recognition methods were developed from four micro-electronic gas sensors for noxious gas mixture analysis. The target gases for the air quality monitoring inside vehicles were two exhaust gases, carbon monoxide (CO) and nitrogen oxides (NOx), and two odor gases, ammonia (NH3) and formaldehyde (HCHO). Four MEMS gas sensors with sensing materials of Pd-SnO2 for CO, In2O3 for NOX, Ru-WO3 for NH3, and hybridized SnO2-ZnO material for HCHO were fabricated. In six binary mixed gas systems with oxidizing and reducing gases, the gas sensing behaviors and the sensor responses of these methods were examined for the discrimination of gas species. The gas sensitivity data was extracted and their patterns were determined using principal component analysis (PCA) techniques. The PCA plot results showed good separation among the mixed gas systems, suggesting that the gas mixture tests for noxious gases and their mixtures could be well classified and discriminated changes.

Original languageEnglish
Pages (from-to)235-241
Number of pages7
JournalKorean Journal of Materials Research
Volume34
Issue number5
DOIs
StatePublished - 2024

Keywords

  • gas mixture
  • gas sensor
  • metal oxide semiconductor
  • pattern recognition
  • sensor array

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