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Nat Commun

Title:		Triboelectric-induced ion mobility for artificial intelligence-enhanced mid-infrared gas spectroscopy
Author(s):		Zhu J; Ji S; Ren Z; Wu W; Zhang Z; Ni Z; Liu L; Zhang Z; Song A; Lee C;
Address:		"School of Mechanical Engineering, Southeast University, Nanjing, 211189, P. R. China. mezhujx@seu.edu.cn. School of Mechanical Engineering, Southeast University, Nanjing, 211189, P. R. 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, P. R. China. School of Instrument Science and Engineering, Southeast University, Nanjing, 211189, P. R. China. 101005200@seu.edu.cn. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117576, Singapore. elelc@nus.edu.sg. Center for Intelligent Sensors and MEMS (CISM), National University of Singapore, Singapore, 117576, Singapore. elelc@nus.edu.sg. NUS Suzhou Research Institute (NUSRI), Suzhou, 215123, P. R. China. elelc@nus.edu.sg"
Journal Title:		Nat Commun
Year:		2023
Volume:		20230502
Issue:		1
Page Number:		2524 -
DOI:		10.1038/s41467-023-38200-6
ISSN/ISBN:		2041-1723 (Electronic) 2041-1723 (Linking)
Abstract:		"Isopropyl alcohol molecules, as a biomarker for anti-virus diagnosis, play a significant role in the area of environmental safety and healthcare relating volatile organic compounds. However, conventional gas molecule detection exhibits dramatic drawbacks, like the strict working conditions of ion mobility methodology and weak light-matter interaction of mid-infrared spectroscopy, yielding limited response of targeted molecules. We propose a synergistic methodology of artificial intelligence-enhanced ion mobility and mid-infrared spectroscopy, leveraging the complementary features from the sensing signal in different dimensions to reach superior accuracy for isopropyl alcohol identification. We pull in 'cold' plasma discharge from triboelectric generator which improves the mid-infrared spectroscopic response of isopropyl alcohol with good regression prediction. Moreover, this synergistic methodology achieves ~99.08% accuracy for a precise gas concentration prediction, even with interferences of different carbon-based gases. The synergistic methodology of artificial intelligence-enhanced system creates mechanism of accurate gas sensing for mixture and regression prediction in healthcare"
Keywords:
Notes:		"PubMed-not-MEDLINEZhu, Jianxiong Ji, Shanling Ren, Zhihao Wu, Wenyu Zhang, Zhihao Ni, Zhonghua Liu, Lei Zhang, Zhisheng Song, Aiguo Lee, Chengkuo eng England 2023/05/03 Nat Commun. 2023 May 2; 14(1):2524. doi: 10.1038/s41467-023-38200-6"