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Selective Detection of Nitrogen-Containing Compound Gases

N-containing gaseous compounds, such as trimethylamine (TMA), triethylamine (TEA), ammonia (NH(3)), nitrogen monoxide (NO), and nitrogen dioxide (NO(2)) exude irritating odors and are harmful to the human respiratory system at high concentrations. In this study, we investigated the sensing responses...

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Detalles Bibliográficos
Autores principales: Yoo, Ran, Lee, Hyun-Sook, Kim, Wonkyung, Park, Yunji, Koo, Aran, Jin, Sang-Hyun, Pham, Thang Viet, Kim, Myung Jong, Maeng, Sunglyul, Lee, Wooyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719914/
https://www.ncbi.nlm.nih.gov/pubmed/31443298
http://dx.doi.org/10.3390/s19163565
Descripción
Sumario:N-containing gaseous compounds, such as trimethylamine (TMA), triethylamine (TEA), ammonia (NH(3)), nitrogen monoxide (NO), and nitrogen dioxide (NO(2)) exude irritating odors and are harmful to the human respiratory system at high concentrations. In this study, we investigated the sensing responses of five sensor materials—Al-doped ZnO (AZO) nanoparticles (NPs), Pt-loaded AZO NPs, a Pt-loaded WO(3) (Pt-WO(3)) thin film, an Au-loaded WO(3) (Au-WO(3)) thin film, and N-doped graphene—to the five aforementioned gases at a concentration of 10 parts per million (ppm). The ZnO- and WO(3)-based materials exhibited n-type semiconducting behavior, and their responses to tertiary amines were significantly higher than those of nitric oxides. The N-doped graphene exhibited p-type semiconducting behavior and responded only to nitric oxides. The Au- and Pt-WO(3) thin films exhibited extremely high responses of approximately 100,000 for 10 ppm of triethylamine (TEA) and approximately −2700 for 10 ppm of NO(2), respectively. These sensing responses are superior to those of previously reported sensors based on semiconducting metal oxides. On the basis of the sensing response results, we drew radar plots, which indicated that selective pattern recognition could be achieved by using the five sensing materials together. Thus, we demonstrated the possibility to distinguish each type of gas by applying the patterns to recognition techniques.