Virtual Sensor Array Based on Piezoelectric Cantilever Resonator for Identification of Volatile Organic Compounds

被引:21
|
作者
Li, Dongsheng [1 ]
Zhu, Boyi [1 ]
Pang, Kai [2 ]
Zhang, Qian [1 ]
Qu, Mengjiao [1 ]
Liu, Weiting [1 ]
Fu, YongQing
Xie, Jin [1 ]
机构
[1] Zhejiang Univ, State Key Lab Fluid Power & Mech Syst, Hangzhou 310027, Zhejiang, Peoples R China
[2] Zhejiang Univ, Dept Polymer Sci & Engn, MOE Key Lab Macromol Synth & Functionalizat, Hangzhou 310027, Peoples R China
基金
国家重点研发计划; 英国工程与自然科学研究理事会; 中国国家自然科学基金;
关键词
AlN piezoelectric cantilever; machine learning; plant diseases diagnosis; virtual sensor array; GRAPHENE OXIDE; ACOUSTIC-WAVE; GAS SENSOR; DISCRIMINATION;
D O I
10.1021/acssensors.2c00442
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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
引用
收藏
页码:1555 / 1563
页数:9
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