湿度
相对湿度
纳米晶
硫化氢传感器
硫黄
六氟化硫
材料科学
气味
二氧化硅
无机化学
分析化学(期刊)
化学工程
二氧化硫
纳米技术
化学
硫化氢
有机化学
环境化学
冶金
工程类
物理
热力学
作者
Yuyan Zhuang,Jintuo Zhu,Danhong Gao,Shasha Gao,Zi‐Jiang Yang,Sheng Huang,Xinjian He
标识
DOI:10.1109/jsen.2023.3329497
摘要
Sulfur dioxide is a colorless gas with strong pungent odor, and prolonged inhalation can damage the respiratory system and heart. Precise measurement of sulfur dioxide is very important for the human health. While the current sulfur dioxide sensor works at a high temperature and is easily interfered by humidity. Therefore, in this work, we used a solution method to coat perovskite nanocrystals Cs3Cu2I5 with metal oxides Fe2O3 and obtained the room-temperature sulfur dioxide gas-sensitive materials Cs3Cu2I5@Fe2O3 nanocrystals. Meanwhile, combined with machine learning, the sensor has the ability of self-calibrating under different humidity environment, realizing the high precision and anti-interference measurement of sulfur dioxide. In addition, in this structure, the coating Fe2O3 not only helps to improve water stability but also transfers the interaction of sulfur dioxide to the inner Cs3Cu2I5 and lowers the gas-sensitive temperature to room temperature. The response/recovery time of the sulfur dioxide sensor based on Cs3Cu2I5@Fe2O3 is 31/816 s, and the sensitivity is 0.19 at 10 ppm. Then, intelligent classification algorithm was used for recognition, and the accurate recognition rate was up to 95.0%. Furthermore, density functional theory (DFT) was implemented to reveal the gas-sensitive mechanism that sulfur dioxide was adsorbed by Cs3Cu2I5@Fe2O3 nanocrystals, the good response was attributed to the band structure changes significantly, and the hybridization of electron orbitals was appeared between gas and nanocrystals. We believe that the sensor will have potential in sulfur dioxide, and the idea of using machine learning to intelligent eliminate humidity interference can also be extended to other gas sensor.
科研通智能强力驱动
Strongly Powered by AbleSci AI