Qualitative and Quantitative Recognition of Volatile Organic Compounds in Their Liquid Phase Based on Terahertz Microfluidic EIT Meta-Sensors

Volatile organic compounds (VOCs) are directly associated with human health concerns and environmental safety. Therefore, it is urgent to achieve accurate detection of VOCs both qualitatively and quantitatively. In this work, the qualitative detection of ethyl benzene (EB), isopropyl alcohol (IPA), and ethyl acetate (EA)-three pure VOCs in liquid phase-was discussed using terahertz (THz) microfluidic electromagnetic-induced transparency (EIT) meta-sensors. The THz response illustrated that with an increase in VOCs' volumes (1-6 mu L), resonant frequencies of dual transmission dips (0.855 and 1.724 THz) and the EIT peak (1.213 THz) exhibited redshift. The limit of detections (LODs) for pure IPA, EA, and EB can achieve 5.45, 13.46, and 4.35 mu g, respectively. The multivariate fusion (MF) model based on the EIT responses to VOCs was utilized to improve the accuracy of trace detection and classification of VOCs. Furthermore, the above method combined with principal component analysis with the Gaussian mixture model (PCA-GMM) and the neural network classification algorithm support vector machine (SVM) was applied to the recognition of VOCs. In addition, the THz method is not feasible to detect trace amounts of VOCs (typically 0.3 mg/L) in wastewater because water is highly absorbable in the THz band and VOCs will evaporate if water is removed. Here, IPA, EA, and EB in soil were detected and classified by PCA-GMM combined with MF. Our results provide a new THz meta-sensor platform to trace the detection of VOCs in the liquid phase and soil and may be used to identify hazardous wastes in illegal dumping.

Automated summary

This study discussed the qualitative detection of three pure VOCs (ethyl benzene, isopropyl alcohol, and ethyl acetate) in liquid phase using terahertz (THz) microfluidic electromagnetic-induced transparency (EIT) meta-sensors. The THz response showed that the resonant frequencies of dual transmission dips and the EIT peak exhibited redshift with an increase in VOCs' volumes. The multivariate fusion (MF) model based on the EIT responses was utilized to improve the accuracy of trace detection and classification of VOCs.