In the gas-sensing mechanism of a metal-oxide-semiconductor (n-type) gas sensor, oxygen adsorption or desorption on the oxide surface leads to an increase or decrease in the resistance of the gas sensor system. Additionally, oxygen can be adsorbed again at the location where initially adsorbed oxygen reacted with the target gas. Thus, the adsorption-desorption equilibrium of the reducing gas on the oxide surface is a significant factor in determining the sensitivity and reaction rate. In particular, for ultralow-concentration gas measurements, the relative concentration of oxygen was very high. To design an ultrasensitive gas sensor, not only the reaction of the target gas but also the competing reaction between the target gas and oxygen must be considered. Although qualitative investigations of these complex relationships have been performed according to the gas concentration and flow rate, reliable quantitative results are limited. In this study, a quantitative approach was used to understand the correlation between oxygen and a target gas by applying data analysis methods. We investigated the behavior of oxygen and the target molecules depending on the gas concentration and flow rate using the parts per billion level of the acetone gas sensor. Initial response data according to various detection conditions were processed using principal component analysis and K-means clustering; as a result, four types of reaction behaviors were inferred for 15 types of reaction conditions. Furthermore, the response time, depending on the detection conditions, can be distinguished using the suggested categorization. Our investigation suggests a possibility beyond simple optimization through the data analysis of the gas-sensing results.
Keywords: SnO2; clustering; flow rate; gas sensors; nanosheets.