气候变化领域集成服务门户(CCPortal): Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis

CCPortal

DOI	10.1016/j.scib.2021.03.021
	Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis
	Zhu J.; Sun Z.; Xu J.; Walczak R.D.; Dziuban J.A.; Lee C.
发表日期	2021
ISSN	20959273
起始页码	1176
结束页码	1185
卷号	66 期号:12
英文摘要	Ion mobility analysis is a well-known analytical technique for identifying gas-phase compounds in fast-response gas-monitoring systems. However, the conventional plasma discharge system is bulky, operates at a high temperature, and inappropriate for volatile organic compounds (VOCs) concentration detection. Therefore, we report a machine learning (ML)-enhanced ion mobility analyzer with a triboelectric-based ionizer, which offers good ion mobility selectivity and VOC recognition ability with a small-sized device and non-strict operating environment. Based on the charge accumulation mechanism, a multi-switched manipulation triboelectric nanogenerator (SM-TENG) can provide a direct current (DC) bias at the order of a few hundred, which can be further leveraged as the power source to obtain a unique and repeatable discharge characteristic of different VOCs, and their mixtures, with a special tip-plate electrode configuration. Aiming to tackle the grand challenge in the detection of multiple VOCs, the ML-enhanced ion mobility analysis method was successfully demonstrated by extracting specific features automatically from ion mobility spectrometry data with ML algorithms, which significantly enhance the detection ability of the SM-TENG based VOC analyzer, showing a portable real-time VOC monitoring solution with rapid response and low power consumption for future internet of things based environmental monitoring applications. © 2021 Science China Press
关键词	Ion mobility Machine learning Plasma discharge Triboelectric nanogenerator Volatile organic compounds
英文关键词	Electric discharges; Gas chromatography; Ion mobility spectrometers; Machine learning; Nanogenerators; Triboelectricity; Volatile organic compounds; Doublers; Fast response; Gas-phases; Ion Mobility; Machine-learning; Mobility analysis; Nanogenerators; Plasma discharge; Triboelectric nanogenerator; Volatile organics; Ions
语种	英语
来源期刊	Science Bulletin
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/207697
作者单位	School of Mechanical Engineering, Southeast University, Nanjing, 211189, China; Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore; Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117576, Singapore; NUS Suzhou Research Institute (NUSRI), Suzhou, 215123, China; Department of Mircroengineering and Photovoltaics, Wroclaw University of Science and Technology, Wroclaw 50-370, Poland; Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, 119077, Singapore
推荐引用方式 GB/T 7714	Zhu J.,Sun Z.,Xu J.,et al. Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis[J],2021,66(12).
APA	Zhu J.,Sun Z.,Xu J.,Walczak R.D.,Dziuban J.A.,&Lee C..(2021).Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis.Science Bulletin,66(12).
MLA	Zhu J.,et al."Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis".Science Bulletin 66.12(2021).