Highly selective detection of ethanol based on hierarchical three-dimensional SnO2: Combining experiment with first-principles calculation

Abstract Improving gas sensing characteristics through the microstructure has attracted more and more attention in recent years. A hierarchical SnO2 nanostructure and its high ethanol selectivity were developed in this work. The hierarchical SnO2 nanostructure was obtained by a facile annealing process using SnS2 nanoflowers as precursor. The SEM and TEM results show that a flower-like SnO2 structure composed of nanoplates forms a hierarchical structure. The hierarchical SnO2 demonstrated excellent response time and high selectivity to ethanol at 200℃. The response/recovery time to 20 ppm ethanol vapor is about 0.75 s and 50 s, respectively. The enhanced sensing properties benefit from its unique structure, including the flower-like hierarchical structure and abundant surface defects, providing more gas active centers and diffusion paths. In order to understand the high selectivity, the first-principles calculations were carried out on the adsorption behavior between SnO2 and various gases. The result demonstrated that SnO2 was theoretically more selective in ethanol than other gases based on the adsorption energy. Humidity test and cycle test effectively prove that the sensor based on SnO2 nanoflower has great prospects for the detection of ethanol.