Your browser doesn't support javascript.
loading
Chemical Discrimination of Benzene Series and Molecular Recognition of the Sensing Process over Ti-Doped Co3O4.
Cao, Zhengmao; Ge, Yingzhu; Wang, Wu; Sheng, Jianping; Zhang, Zijian; Li, Jieyuan; Sun, Yanjuan; Dong, Fan.
Afiliación
  • Cao Z; Research Center for Environmental and Energy Catalysis, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Ge Y; School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Wang W; School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Sheng J; School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Zhang Z; School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Li J; Research Center for Environmental and Energy Catalysis, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Sun Y; School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China.
  • Dong F; Research Center for Environmental and Energy Catalysis, Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
ACS Sens ; 7(6): 1757-1765, 2022 Jun 24.
Article en En | MEDLINE | ID: mdl-35657691
This work achieved the chemical discrimination of benzene series (toluene, xylene isomers, and ethylbenzene gases) based on the Ti-doped Co3O4 sensor. Benzene series gases presented different gas-response features due to the differences in redox rate on the surface of the Ti-doped Co3O4 sensor, which created an opportunity to discriminate benzene series via the algorithm analysis. Excellent groupings were obtained via the principal component analysis. High prediction accuracies were acquired via k-nearest neighbors, linear discrimination analysis (LDA), and support vector machine classifiers. With the confusion matrix for the data set using the LDA classifier, the benzene series have been well classified with 100% accuracy. Furthermore, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and density functional theory calculations were conducted to investigate the molecular gas-solid interfacial sensing mechanism. Ti-doped Co3O4 showed strong Lewis acid sites and adsorption capability toward reaction species, which benefited the toluene gas-sensing reaction and resulted in the highly boosted gas-sensing performance. Our research proposed a facile distinction methodology to recognize similar gases and provided new insights into the recognition of gas-solid interfacial sensing mechanisms.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Sens Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Sens Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos