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

Li, Dongsheng, Zhu, Baoyi, Pang, Kai, Zhang, Qian, Qu, Mengjiao, Liu, Weiting, Fu, Yong Qing and Xie, Jin (2022) Virtual Sensor Array Based on Piezoelectric Cantilever Resonator for Identification of Volatile Organic Compounds. ACS Sensors. ISSN 2379-3694 (In Press)

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Official URL: https://doi.org/10.1021/acssensors.2c00442

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 based on 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 limit of detections (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 multi-dimensional responses generate a unique fingerprint for each VOC. Based on 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

Item Type: Article
Uncontrolled Keywords: AlN piezoelectric cantilever, Machine learning, Plant diseases diagnosis, Virtual sensor array, VOC identification
Subjects: H300 Mechanical Engineering
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: Rachel Branson
Date Deposited: 04 May 2022 08:23
Last Modified: 18 May 2022 13:00
URI: http://nrl.northumbria.ac.uk/id/eprint/49024

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