纳微快报(英文)2021,Vol.13Issue(4):146-158,13.
Berlin Green Framework-Based Gas Sensor for Room-Temperature and High-Selectivity Detection of Ammonia
Berlin Green Framework?Based Gas Sensor for Room?Temperature and High?Selectivity Detection of Ammonia
摘要
Abstract
Ammonia detection possesses great potential in atmos-phere environmental protection, agriculture, industry, and rapid medical diagnosis. However, it still remains a great challenge to balance the sensitivity, selectivity, working temperature, and response/recovery speed. In this work, Berlin green (BG) framework is demonstrated as a highly promising sensing material for ammonia detection by both den-sity functional theory simulation and experimental gas sensing investiga-tion. Vacancy in BG framework offers abundant active sites for ammonia absorption, and the absorbed ammonia transfers sufficient electron to BG, arousing remarkable enhancement of resistance. Pristine BG framework shows remarkable response to ammonia at 50–110 ℃ with the highest response at 80 ℃, which is jointly influenced by ammonia's absorption onto BG surface and insertion into BG lattice. The sensing performance of BG can hardly be achieved at room temperature due to its high resistance. Introduction of conductive Ti3CN MXene overcomes the high resistance of pure BG framework, and the simply prepared BG/Ti3CN mixture shows high selectivity to ammonia at room temperature with satisfying response/recovery speed.关键词
Berlin green framework/Gas sensor/Ammonia/Room temperature/High selectivityKey words
Berlin green framework/Gas sensor/Ammonia/Room temperature/High selectivity引用本文复制引用
Tingqiang Yang,Lingfeng Gao,Wenxuan Wang,Jianlong Kang,Guanghui Zhao,Delong Li,Wen Chen,Han Zhang..Berlin Green Framework-Based Gas Sensor for Room-Temperature and High-Selectivity Detection of Ammonia[J].纳微快报(英文),2021,13(4):146-158,13.基金项目
The research was supported by the NationalNatural Science Foundation of China (Grant Nos. 61435010, 61675135, and 62005177), the National Natural Science Foun-dation for Young Scientists of China (Grant No. 61905161), and the Science and Technology Innovation Commission of Shenzhen (JCYJ20190808142415003). Authors also acknowledge the sup-port from Instrumental Analysis Center of Shenzhen University (Xili Campus). (Grant Nos. 61435010, 61675135, and 62005177)