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ACS Sens

Title:		Virtual Sensor Array Based on Piezoelectric Cantilever Resonator for Identification of Volatile Organic Compounds
Author(s):		Li D; Zhu B; Pang K; Zhang Q; Qu M; Liu W; Fu Y; Xie J;
Address:		"State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou, Zhejiang 310027, People's Republic of China. MOE Key Laboratory of Macromolecular Synthesis and Functionalization, Department of Polymer Science and Engineering, Zhejiang University, 38 Zheda Road, Hangzhou 310027, People's Republic of China. Faculty of Engineering and Environment, University of Northumbria, Newcastle upon Tyne NE1 8ST, United Kingdom"
Journal Title:		ACS Sens
Year:		2022
Volume:		20220512
Issue:		5
Page Number:		1555 - 1563
DOI:		10.1021/acssensors.2c00442
ISSN/ISBN:		2379-3694 (Electronic) 2379-3694 (Linking)
Abstract:		"Piezoelectric cantilever resonator is one of the most promising platforms for real-time sensing of volatile organic compounds (VOCs). However, it has been a great challenge to eliminate the cross-sensitivity of various VOCs for these cantilever-based VOC sensors. Herein, a virtual sensor array (VSA) is proposed on the basis of a sensing layer of GO film deposited onto an AlN piezoelectric cantilever with five groups of top electrodes for identification of various VOCs. Different groups of top electrodes are applied to obtain high amplitudes of multiple resonance peaks for the cantilever, thus achieving low limits of detection (LODs) to VOCs. Frequency shifts of multiple resonant modes and changes of impedance values are taken as the responses of the proposed VSA to VOCs, and these multidimensional responses generate a unique fingerprint for each VOC. On the basis of machine learning algorithms, the proposed VSA can accurately identify different types of VOCs and mixtures with accuracies of 95.8 and 87.5%, respectively. Furthermore, the VSA has successfully been applied to identify the emissions from healthy plants and 'plants with late blight' with an accuracy of 89%. The high levels of identifications show great potentials of the VSA for diagnosis of infectious plant diseases by detecting VOC biomarkers"
Keywords:		Biomarkers Plants *Volatile Organic Compounds AlN piezoelectric cantilever VOC identification machine learning plant diseases diagnosis virtual sensor array;
Notes:		"MedlineLi, Dongsheng Zhu, Boyi Pang, Kai Zhang, Qian Qu, Mengjiao Liu, Weiting Fu, YongQing Xie, Jin eng Research Support, Non-U.S. Gov't 2022/05/14 ACS Sens. 2022 May 27; 7(5):1555-1563. doi: 10.1021/acssensors.2c00442. Epub 2022 May 12"