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Hierarchical SnO2/NiO microflowers via heterojunction engineering for high-sensitive ppb-level xylene detection
Lele Ma1, Qi Lei1, Xiaowen Zhang1
1School of Resources, Environment and Materials, Guangxi University, Nanning, 530004, China; Guangxi Key Laboratory of Processing for Non-Ferrous Metals and Featured Materials, Guangxi University, Nanning, 530004, China; Key Laboratory of Environmental Protection (Guangxi University), Education Department of Guangxi Zhuang Autonomous Region, Guangxi, Nanning, 530004, China.
None:
Xylene, as a typical toxic volatile organic compound (VOC), requires trace-level monitoring for environmental and health protection. However, existing xylene gas sensors face challenges such as high operating temperatures, insufficient sensitivity, and cross-interference from aromatic hydrocarbons. In this research, SnO2/NiO heterojunctions were synthesized using a solvothermal approach, and a comprehensive evaluation of their gas-sensing capabilities toward xylene was conducted. The findings reveal that the response of the 15 mol% SnO2/NiO gas sensor is 24 at the optimal working temperature of 180 °C to 100 ppm xylene, a value 15 times greater than the response observed for NiO under the same conditions. Moreover, the 15 mol% SnO2/NiO gas sensor demonstrates exceptional sensing performance, featuring an impressively low detection limit of 50 ppb. It also demonstrates remarkable selectivity, consistent repeatability, and strong long-term stability, making it highly reliable for extended use. The improved sensing performance for xylene originates from the synergistic effects of the p-n heterojunction formed by NiO and SnO2, along with the catalytic properties, which collectively improve oxygen species adsorption, facilitate gas molecule diffusion, and selectively activate target gas molecules. This study proposes a novel strategy to address the selectivity bottleneck in aromatic hydrocarbons detection, laying a theoretical foundation for high-performance VOC monitoring devices in complex environments.
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