Development of ZnO-doped SnO2 sensor for Detection of SO2 and Performance Validation through Artificial Neural Network - K. Srivastava, Jitendra; Kumar Verma, Deepak (International Journal of Computer Sciences and Engineering, 2021)
In the present work we have fabricated a thick film SnO2 sensor on a 1˝x1˝ alumina substrate. It consists of a gas sensitive layer (SnO2) doped with ZnO, a pair of electrodes underneath the gas sensing layer serving as a contact pad for sensor and a heater element on the backside of the substrate was printed. The sensitivity of sensor has been studied and measured at different temperatures (1500C - 3500C) upon exposure to SO2. An approach is made to measure the sensitivity of ZnO-doped SnO2 by using Artificial Neural Network tool. Finally we have shown the results that shows the potential of Artificial Neural Network as a design tool in the area of thick film gas sensor fabrication and development.