General modeling of graphene field-effect biosensors: Application to label-free DNA hybridization detection

Abstract

This work presents a unified, physics-based modeling framework for predicting the electrical response of graphene-based f ield-effect biosensors (BioGFETs) under steady-state conditions, encompassing both electrolyte–semiconductor (ES) and elec trolyte–insulator–semiconductor (EIS) configurations. The biomolecular layer is represented as a charged, ion-permeable membrane, enabling a consistent treatment of diverse biofunctionalization strategies. The model self-consistently captures electrolyte electro statics, including nonlinear screening effects and surface charge regulation arising from protonation and deprotonation processes, which play a central role in the electrostatic transduction of biomolecular interactions. These interfacial effects are coupled to a physics-based large-signal model of carrier transport in the graphene channel, allowing direct computation of the sensor electrical response under well-defined electrochemical sensing conditions. The resulting approach provides a compact, circuit-compatible description of BioGFET operation suitable for device- and circuit-level analysis. Implemented in Verilog-A, the framework is fully compatible with standard SPICE-like simulation tools, enabling device-circuit co-design. Model predictions show excellent agreement with experimental data reported for ES and EIS graphene BioGFETS operating as pH sensors and for label-free DNA hybridization detection. By combining electrochemical interface modeling with graphene channel transport within a unified compact framework, this work provides a robust and versatile CAD-oriented tool for the analysis and optimization of graphene-based BioGFET sensing platforms.