Graphene Chemical Vapor Sensors with Excellent Discrimination

Abstract: Graphene is very attractive for chemical vapor sensor applications due to its flexible, atomically thin structure and unique electronic properties. I will report our research on two-terminal graphene chemical sensors with and without surface engineering. The goal of this project is to develop precise and efficient transient characterization and feature analysis technology to identify different chemicals with similar physical structures and chemical properties. The devices were fully characterized with different chemical vapors, such as hydrocarbon compounds consisting of toluene, o-xylene, p-xylene, and mesitylene. The analysis depending on maximum response change will cause confusion during chemical discrimination and classification. Our strategy is to analyze the measurement data with transient feature analysis to discriminate the different species of chemical vapors by using principle component analysis (PCA). To further increase the precision of discrimination, cross-active sensors and sensor networks with different coating polymers have also been designed and studied. The result indicates that PCA has much higher discrimination precision than the conventional method, and very interestingly, cross-active sensor arrays can significantly improve chemical discrimination.