Enhanced Gas Sensing Performance of CuO-ZnO Composite Nanostructures for Low-Concentration NO2 Detection

Hakimeh Pakdel, Matteo Borsi, Massimo Ponzoni,Elisabetta Comini

Chemosensors(2024)

引用 0|浏览0
暂无评分
摘要
The detection of nitrogen dioxide (NO2) is essential for safeguarding human health and addressing environmental sustainability. That is why, in the last decades, gas sensors have been developed to detect NO2 to overcome these hazards. This study explores the use of a novel CuO-ZnO composite synthesized through a polyol and sol–gel technique to enhance gas sensing performance. The CuO-ZnO composite offers the advantage of a synergic combination of its properties, leading to improved sensitivity, selectivity, and low detection limit. The innovative polyol technique employed in this research enables the controlled synthesis of hierarchical CuO and porous ZnO structures. The composite formation is achieved using the sol–gel method, resulting in CuO-ZnO composites with different ratios. The structural, morphological, and optical properties of the materials have been characterized using FESEM, X-ray diffraction, and UV-vis spectroscopy. Gas sensing experiments demonstrate enhanced performance, particularly in sensitivity and selectivity for NO2, even at low concentrations. The composites also exhibit improved baseline stability compared to pristine CuO and ZnO. This study explains the influence of humidity on gas sensing properties by examining interactions between water molecules and sensor surfaces. Notably, the developed CuO-ZnO composite displays excellent selectivity towards NO2, attributed to favorable bonding characteristics and acid-base properties. Overall, this research contributes to advancing gas sensor technology, providing a promising potential for sensitive and selective NO2 detection, thereby addressing critical needs for human health and environmental protection.
更多
查看译文
关键词
CuO-ZnO composite,NO<sub>2</sub>,gas sensor,gas sensing performance,selectivity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要