High Data Dimensionality of Virtual Sensor Array Based on QCM and MXene for Selective VOC Detection

Virtual sensor array (VSA) has been developed for selective detection of VOCs. Currently the most reported VSAs only detect the change of a single property of the sensing film, thus a serious waste of valuable information. Herein, we propose a VSA with a high data dimensionality based on QCM and a sensing layer of MXene. Mechanical and electrical properties of the MXene film are detected simultaneously by the QCM with appropriate sizes of sensing film and electrodes. We take changes of the extracted parameters from Butterworth-van-Dyke (BvD) equivalent circuit obtained at multiple harmonics as the response of the QCM-based VSA after exposure to various VOCs. By performing the principal component analysis (PCA) for the response of the VSA, we demonstrate the data dimensionality over 4-D of the VSA is achieved. And the proposed VSA has a potential to distinguish between different VOCs and quantify concentrations of target VOCs.