An electronic nose based on carbon nanotube-titanium dioxide hybrid nanostructures for detection and discrimination of volatile organic compounds

Detection and classification of Volatile Organic Compounds (VOCs) that pose risks to human health even at very low concentrations, is a common requirement in the industry. Herein, we apply a modification to the aligned Carbon Nanotubes (CNTs) grown at low temperature (250 ?) using Plasma Enhanced Chemical Vapor Deposition (PECVD). CNTs are used to identify VOCs in an improved sensitivity condition to gas at room temperature. We improve the sensitivity and stability of carbon nanotube sensors via growing Titanium Dioxide Nanowires (TiO2-NW) on the surface of CNTs through the hydrothermal method. A threefold increase in sensitivity and a 30 second decrease in response time were observed as a result of the CNT-TiO2 sensor compared to the pristine CNT sensor. In order to obtain new data, we deposit four different electrodes on the TiO2 surface as virtual arrays of Electronic nose (E-nose). Temperature modulation and Discrete Wavelet Transform (DWT) of virtual arrays, extract new features of the E-nose data. We select 14 different features from E-nose data and apply Principle Component Analysis (PCA) method for data reduction. We categorize the extracted features by using Support Vector Machine (SVM) algorithms and data covariance properties. This paper achieves 97.5% accuracy in classifying four different VOC gases.

Automated summary

This paper presents a modification to carbon nanotubes (CNTs) to improve the sensitivity to volatile organic compounds (VOCs) and enhance the stability of CNT sensors. By growing titanium dioxide nanowires (TiO2-NW) on the surface of CNTs, the sensors show increased sensitivity and reduced response time. Using virtual arrays of an electronic nose (E-nose), new features are extracted from the data and classified using support vector machine (SVM) algorithms. The paper achieves high accuracy in classifying different VOC gases.