Selective sensing and mechanism of patterned graphene-based sensors: Experiments and DFT calculations

Abstract Graphene with antidots shows great potential in wearable devices and highly sensitive sensors. In this paper, we fabricated the patterned graphenes of circle, square, and triangle by ultrafast laser processing. The given patterned graphene can precisely detect one specific gas from the CO/NO/H2O-mixed gases. The sensing performance results demonstrated that the circle patterned graphene (cir-graphene) was most sensitive to CO with the highest sensitivity with the gauge factor (GF) of 3.9 × 104. For NO sensing, the triangle patterned graphene (tri-graphene) conducted the best results. The square patterned graphene (squ-graphene) was the most sensitive to H2O. The DFT calculations revealed that CO was chemical adsorbed on cir-graphene with the most negative adsorption energy (−3.638 eV). For NO sensing, tri-graphene performed best. While, the patterned graphene was not available to H2O sensing. This work offers a novel solution to next-generation wearable multifunctional sensors, and a new insight for the selective sensing mechanism.