Fabrication of a low background signal glucose biosensor with 3D network materials as the electrocatalyst.

Glucose oxidase (GOx) based biosensor is an effective method to determine glucose level. However, the biosensors embedded with high electroactive species suffered from high background signal levels, which leading to relative low sensitivity for glucose sensing. In this work, a novel 3D network materials based glucose biosensor with low background signal was constructed, which demonstrated high sensitivity and selectivity towards glucose assay. Here, the combination of ionic liquid modified graphene sheets (GS-IL) and Au nanorods (Au NRs) acted as high electroactive catalyst, and thiol-containing silica sol-gel served as a nonconductive matrix to self-assembly of GS-IL and Au NRs to form the three-dimensional (3D) network materials. Meanwhile, the doping amount of the sol-gel had significant influences on electrochemical performance of the 3D network materials based biosensor. As a result, optimized 3.75% doping 3D network materials were selected to construct the glucose biosensor, which exhibited low background signal and high sensitivity. This biosensor was successfully applied in monitoring the glucose levels of serum and brain microdialysate samples.