Virtual sensor array based on MXene for selective detections of VOCs

Two-dimensional transition metal carbides/nitrides, known as MXenes, have recently received significant attention for gas sensing applications. However, MXenes have strong adsorption to many types of volatile organic compounds (VOCs), and therefore gas sensors based on MXenes generally have low selectivity and poor performance in mixtures of VOCs due to cross-sensitivity issues. Herein, we developed a Ti3C2Tx-based virtual sensor array (VSA) which allows both highly accurate detection and identification of different VOCs, as well as concentration prediction of the target VOC in variable backgrounds. The VSA's responses from the broadband impedance spectra create a unique fingerprint of each VOC without a need for changing temperatures. Based on the methodologies of principal component analysis and linear discrimination analysis, we demonstrate highly accurate identifications for different types of VOCs and mixtures using this MXene based VSA. Furthermore, we demonstrate an accuracy of 93.2% for the prediction of ethanol concentrations in the presence of different concentrations of water and methanol. The high level of identification and concentration prediction shows a great potential of MXene based VSA for detection of VOCs of interest in the presence of known and unknown interferences.

Automated summary

The research developed a Ti3C2Tx-based virtual sensor array (VSA) for highly accurate detection and identification of different VOCs, as well as concentration prediction. The VSA creates a unique fingerprint of each VOC based on the responses from broadband impedance spectra.