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A Highly Selective Acetone Sensor Based on Coal-Based Carbon/MoO2 Nanohybrid Material.
Zhang, Min; Han, Yi; Liu, Ting; Jia, Hongguang.
Afiliação
  • Zhang M; School of Physics Science and Technology, Xinjiang University, Urumqi 830046, China.
  • Han Y; School of Physics Science and Technology, Xinjiang University, Urumqi 830046, China.
  • Liu T; College of Chemistry, Xinjiang University, Urumqi 830046, China.
  • Jia H; School of Physics Science and Technology, Xinjiang University, Urumqi 830046, China.
Sensors (Basel) ; 24(13)2024 Jul 03.
Article em En | MEDLINE | ID: mdl-39001099
ABSTRACT
High temperature represents a critical constraint in the development of gas sensors. Therefore, investigating gas sensors operating at room temperature holds significant practical importance. In this study, coal-based porous carbon (C-700) and coal-based C/MoO2 nanohybrid materials were synthesized using a simple one-step vapor deposition and sintering method, and their gas-sensing performance was investigated. The gas-sensing performance for several VOC gases (phenol, ethyl acetate, ethanol, acetone, triethylamine, and toluene) and a 95% RH high-humidity environment were tested. The results indicated that the C/MoO2-450 sample sintered at 450 °C exhibited excellent specific selectivity towards acetone at room temperature, with a response value of 4153.09% and response/recovery times of 10.8 s and 2.9 s, respectively. Furthermore, the C/MoO2-450 sample also demonstrated good repeatability and long-term stability. The sensing mechanism of the synthesized materials was also explored. The superior gas-sensing performance can be attributed to the synergistic effect between the porous carbon and MoO2 nanoparticles. Given the importance of enhancing the high-tech and high-value-added utilization of coal, this study provides a viable approach for utilizing coal-based carbon materials in detecting volatile organic compounds at room temperature.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article