挥发性有机化合物
材料科学
响应时间
纳米技术
计算机科学
化学
有机化学
计算机图形学(图像)
作者
Mohammad Reza Mohammadzadeh,Amirhossein Hasani,Keyvan Jaferzadeh,Mirette Fawzy,Thushani De Silva,Amin Abnavi,Ribwar Ahmadi,Hamidreza Ghanbari,Abdelrahman M. Askar,Fahmid Kabir,R. K. N. D. Rajapakse,Michael M. Adachi
出处
期刊:Advanced Science
[Wiley]
日期:2023-01-19
卷期号:10 (10): e2205458-e2205458
被引量:26
标识
DOI:10.1002/advs.202205458
摘要
Abstract Volatile organic compounds (VOCs) sensors have a broad range of applications including healthcare, process control, and air quality analysis. There are a variety of techniques for detecting VOCs such as optical, acoustic, electrochemical, and chemiresistive sensors. However, existing commercial VOC detectors have drawbacks such as high cost, large size, or lack of selectivity. Herein, a new sensing mechanism is demonstrated based on surface interactions between VOC and UV‐excited 2D germanium sulfide (GeS), which provides an effective solution to distinguish VOCs. The GeS sensor shows a unique time‐resolved electrical response to different VOC species, facilitating identification and qualitative measurement of VOCs. Moreover, machine learning is utilized to distinguish VOC species from their dynamic response via visualization with high accuracy. The proposed approach demonstrates the potential of 2D GeS as a promising candidate for selective miniature VOCs sensors in critical applications such as non‐invasive diagnosis of diseases and health monitoring.
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