Gas sensor based on defective graphene/pristine graphene hybrid towards high sensitivity detection of NO2

Abstract

We propose an approach to improve the performance of graphene-based gas sensors by the integration of defective graphene with pristine graphene. The defect density of defective graphene is controlled by the fluence of Si+ implantation, and an H2 etching process is utilized to tune defect size. As defects are able to adsorb target gas efficiently, the response of graphene-based sensors was improved remarkably with the controllable defect density. The response sensitivity of a defective-graphene-based sensor to concentrations of NO2 at 100 ppm can be as high as 248%, 13 times higher than that of a sensor built using pristine graphene. In addition, defective-graphene-based sensors exhibit high response and recovery rates at room temperature, which is comparable to those of pristine graphene-based sensors and faster than conventional defect-decorated graphene sensors. Most importantly, defective-graphene-based gas sensors exhibit excellent reproducibility, stability, and selectivity. Our study suggests a simple and effective strategy for the mass production of high-performance graphene-based gas sensors for NO2 gas detection.