Issue 29, 2022

ZnO@CuO hollow nanosphere-based composites used for the sensitive detection of hydrogen sulfide with long-term stability

Abstract

In this study, zinc oxide@cupric oxide hollow nanospheres (ZnO@CuO HNS, 330 nm in diameter) were successfully prepared by a hard-template method using amino-phenolformaldehyde resin spheres (APF) as the templates. A new type of thin-film gas sensor toward hydrogen sulfide (H2S) was fabricated by means of drop-coating on the gold electrode of an alumina ceramic tube. The microstructure and morphology of the nanosphere composites were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and the gas-sensing performance of the composites toward the detection of H2S were investigated. The ZnO@CuO nanocomposite with a hollow structure exhibited good gas-sensing properties. Under the optimum operating temperature of 260 °C, ambient temperature of 30 °C, and ambient humidity of 70%, the linear response of the sensor to H2S was in the concentration range of 0.1–100 ppm, and its detection limit reached 0.0611 ppm, with a quick response time of 78 s. Also, the sensor possessed good repeatability, selectivity, and stability. The long-term stability and run duration of such sensors were pronounced, with only a 1.9% reduction in the signal after the continuous monitoring of H2S gas in a pig farm for 18 months using Alibaba's cloud remote transmission system, which presents an important practical application prospect in atmosphere environment monitoring on livestock-raising fields.

Graphical abstract: ZnO@CuO hollow nanosphere-based composites used for the sensitive detection of hydrogen sulfide with long-term stability

Article information

Article type
Paper
Submitted
26 May 2022
Accepted
27 Jun 2022
First published
05 Jul 2022

Anal. Methods, 2022,14, 2866-2875

ZnO@CuO hollow nanosphere-based composites used for the sensitive detection of hydrogen sulfide with long-term stability

Y. Tang, Y. Huang, H. Zou, L. Wu, Z. Xiao, J. Zeng, L. Sun, D. Yu and Z. Cao, Anal. Methods, 2022, 14, 2866 DOI: 10.1039/D2AY00847E

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