Statistical Analysis of the Influence of Various Types of Graphite Precursors and Oxidation Methods on the Gas Sensor Properties of Reduced Graphene Oxide

Abstract

The fabrication process of reduced graphene oxide depends on many factors (e.g., graphite precursor, methods of oxidation, reduction, and exfoliation) which have a significant influence on the properties of this material. Therefore, their selection is not easy due to the large number of possible combinations of these factors. To overcome this problem, we proposed to use a multivariate analysis of variance method of finding associations between the qualitative type of independent variables and the quantitative type of dependent variable. Using ANOVA, we showed that the combination (interaction) of these variables is more important than the individual influence of the variables on the fabricated rGO. Knowing how the particular variables and their combinations affect the properties of rGO, it is easier to plan the fabrication process of this material. In this paper, we analyzed the number of oxide layers and designated the most promising oxides in terms of sensor gas application. Independently, we fabricated chemiresistor sensors and studied their response to NO2 in the analyzed atmosphere. We were able to combine the experimental results with statistical analysis indicating which oxidation methods and which graphite precursors will provide the best sensitivity.