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

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