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Pulsed Airstream-Driven Hierarchical Micro-Nano Pore Structured Triboelectric Nanogenerator for Wireless Self-Powered Formaldehyde Sensing.
Wang, Gang; Ren, Zhongkan; Zheng, Longkui; Kang, Yajie; Luo, Ning; Qiao, Zhuhui.
Afiliación
  • Wang G; Shandong Laboratory of Advanced Material and Green Manufacturing at Yantai, Yantai, 264006, P. R. China.
  • Ren Z; School of Chemistry and Materials Science, Ludong University, Yantai, 264025, P. R. China.
  • Zheng L; Shandong Laboratory of Advanced Material and Green Manufacturing at Yantai, Yantai, 264006, P. R. China.
  • Kang Y; School of Environmental and Material Engineering, Yantai University, Yantai, 264005, P. R. China.
  • Luo N; School of Environmental and Material Engineering, Yantai University, Yantai, 264005, P. R. China.
  • Qiao Z; School of Environmental and Material Engineering, Yantai University, Yantai, 264005, P. R. China.
Small ; : e2406500, 2024 Aug 14.
Article en En | MEDLINE | ID: mdl-39139056
ABSTRACT
Formaldehyde (HCHO), as a common volatile organic compound, has a serious impact on human health in the daily lives and industrial production scenarios. Given the security issue of HCHO detection and danger warning, a ZIF-8/copper foam based pulsed airstream-driven triboelectric nanogenerator (ZCP-TENG) is designed to develop the self-powered HCHO sensors. By combining contact electrification and electrostatic induction, the ZCP-TENG can be utilized for airflow energy harvesting and HCHO concentration detection. The short-circuit current and output power of the ZCP-TENG can reach 2.0 µA and 81 µW (20 ppm). With the high surface area, abundant micro-nano pores, and excellent permeation flux, the ZCP-TENGs exhibit excellent HCHO sensing response (61.3% at 100 ppm), low detection limit (≈2 ppm), and rapid response/recovery time (14/15 s), which can be served as a highly sensitive and selective HCHO sensor. By connecting an intelligent wireless alarm, the ZCP-TENGs are designed to construct a self-powered warning system to monitor and remind the HCHO of exceedance situations. Moreover, by combining a support vector machine model, the difference concentrations can be quickly identified with an average prediction accuracy of 100%. This study illustrates that ZCP-TENGs have broad application prospects and provide guidance for HCHO monitoring and danger warnings.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Small Asunto de la revista: ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Small Asunto de la revista: ENGENHARIA BIOMEDICA Año: 2024 Tipo del documento: Article Pais de publicación: Alemania