首页|Smart mask based on lead-free perovskite humidity sensor for labor intensity grading by breath monitoring

Smart mask based on lead-free perovskite humidity sensor for labor intensity grading by breath monitoring

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  • NETL
  • NSTL
  • Elsevier
Unaware fatigue causes inefficiencies and unsafe behaviors. Therefore, an easily-used technique to monitor labor intensity is critical. In this work, the humidity-sensitive material Cs_3Cu_2I_5 was used to monitor breath and grade labor intensity without contact. The Cs_3Cu_2I_5 showed reversible conversion to the CsCu_2I_3 phase by being exposed to water. EMI-TFSI was added to improve the material's conductivity and electrochemical stability, helping to passivate surface defects and adjust the response sensitivity. Further mechanism explanation was explored by density functional theory calculation and electrochemical impedance spectroscopy. Switching from 40 % RH to 90 % RH, the sensor resistance changed by 161.3 megohms with a relative change ratio of 0.967. Besides, the sensor has a short response/recovery time (e.g., 2.0/0.5 s switching from 40 % RH to 60 % RH), with good repeatability and stability in high humidity. Then, the developed high-performance lead-free sensor was integrated into a smart mask with a neural network algorithm to monitor and forecast breath, and grade labor intensity. The model was built with 240 sample data and 19 constructed features. The accuracy of identifying three intensity levels in external validation was 0.9. Based on the sensing data and the grading model, a real-time labor intensity monitoring and visualization platform was constructed.

PerovskiteHumidity sensingOccupational fatigueSmart maskNeural network

Wufan Xuan、Yuyang Chen、Dunan Hu、Xinran Gao、Sheng Huang

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School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China

School of Materials Science and Physics, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China

School of Materials Science and Physics, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China, Institute for Superconducting and Electronic Materials (ISEM), Australian Institute for Innovative Materials (AIIM) Innovation Campus, University of Wollongong, Squires Wayl, North Wollongong, NSW 2500, Australia

School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China, School of Materials Science and Physics, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China

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2023

10.1016/j.snb.2023.134622

Sensors and actuators, B. Chemical

Sensors and actuators, B. Chemical

ISSN：0925-4005
年,卷(期)：2023.397(Dec.)
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