Virtual sensor array based on Butterworth-Van-Dyke equivalent model of QCM for selective detection of volatile organic compounds

Li, Dongsheng, Xie, Zihao, Qu, Mengjiao, Zhang, Qian, Fu, Richard and Xie, Jin (2021) Virtual sensor array based on Butterworth-Van-Dyke equivalent model of QCM for selective detection of volatile organic compounds. ACS Applied Materials & Interfaces, 13 (39). pp. 47043-47051. ISSN 1944-8244

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Official URL: https://doi.org/10.1021/acsami.1c13046

Abstract

Recently virtual sensor arrays(VSAs) have been developed to improve the selectivity of volatile organic compound (VOC)sensors. However, most reported VSAs rely on detecting single property change of the sensing material after their exposure to VOCs, thus resulting in loss of much valuable information. In this work, we propose a VSA with a high dimensionality of outputs based on a quartz crystal microbalance (QCM) and a sensing layer of MXene. Changes in both mechanical and electrical properties of the MXene film are utilized in detection of the VOCs. We take the changes of parameters of the Butterworth-Van-Dyke model for the QCM-based sensor operated at multiple harmonics as the responses of the VSA to various VOCs. Dimensionality of the VSA’s responses has been expanded to four independent outputs, and the responses to the VOCs have shown a good linearity in multidimensional space. The response and recovery times are 16 s and 54 s, respectively. Based on machine learning algorithms, the proposed VSA accurately identifies different VOCs and mixtures, as well as quantifies the targeted VOC in complex backgrounds (with an accuracy of 90.6). Moreover, we demonstrate the capacity of the VSA to identify “patients with diabetic ketosis” from volunteers with an accuracy of 95, based on detection of their exhaled breath. The QCM-based VSA shows a great potential for detecting VOC biomarkers in human breath for disease diagnosis.

Item Type: Article
Additional Information: Funding information: This work is supported by the “National Natural Science Foundation of China (NSFC 51875521)”, the “Zhejiang Provincial Natural Science Foundation of China (LZ19E050002)”, the “Science Fund for Creative Research Groups of National Natural Science Foundation of China (51821093)”, and International Exchange Grant (IEC/NSFC/201078) through Royal Society UK and the NSFC.
Uncontrolled Keywords: VOCs sensor, Selectivity, Virtual sensor array, QCM, MXene, Breath analysis
Subjects: H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User: John Coen
Date Deposited: 13 Sep 2021 10:37
Last Modified: 20 Oct 2021 13:45
URI: http://nrl.northumbria.ac.uk/id/eprint/47144

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