Method of sieving the optimal NO2 sensitive material

NO2 is the representative pollutant in air quality monitoring and power industry. Although numerous gas sensors have been employed for the accurate detection of NO2, a universal method sieving for the optimum sensor is still lacked. Herein, a strategy to acquire the optimal NO2-sensitive material has been proposed, and a series of tests verified its effectiveness. First, the serious noise would exist in the gas sensors with the high resistivity, so an appropriate baseline resistance is the basis for the practical application. Furthermore, the performances of SnCl2- In2O3 doped with six metal oxides (CuO, NiO, TiO2, SnO2, WO3, ZnO) on NO2 were investigated. The quantitative evaluation method that integrated the variation coefficient method (VCM), the technique for order preference by similarity to ideal solution (TOPSIS), and the grey correlation analysis (GRA) has been proposed to solve the imbalance of sensors' indices. Due to the highest comprehensive score, 10 wt% WO3-doped SnCl2-In2O3 with high response value (5962.20%) was regarded as the optimum for NO2 detection. Ultimately, an additional comparative test among the as-prepared sensors, previous investigations and commercial devices has demon-strated the great potential of the method in practice.