Predicting the Level of Background Current Noise in Graphene Biosensor through a Non-Covalent Functionalization Process

Abstract

The rapid worldwide spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a series of problems. Detection platforms based on graphene field-effect transistors (GFETs) have been proposed to achieve a rapid diagnosis of SARS-CoV-2 antigen or antibody. For GFET-based biosensors, the graphene surface usually needs to be functionalized to immobilize the bioreceptor and the non-covalent approach is preferred for functionalization because it is believed not to significantly alter the electronic properties of graphene. However, in this work, the non-covalent functionalization introduced by 1-pyrenebutyric acid N-hydroxysuccinimide ester (PBASE) was determined to lead to different changes in electrical properties in graphene samples with different defect densities. The fabricated graphene biosensor can successfully detect SARS-CoV-2 antigen with a concentration as low as 0.91 pg/mL. Further, by careful comparison, we determined that, for GFET fabricated on graphene with a higher defect density, the current variation caused by PBASE modification is greater and the background current noise in the subsequent antigen detection is also larger. Based on this relationship, we can predict the background current noise of the biosensors by evaluating the current change induced by the modification and screen the devices at an early stage of graphene biosensor fabrication for process optimization.