Analyte-class-dependent electrostatic–transport coupling in graphene FET biosensors

The transfer curve of a graphene field-effect transistor (GFET) biosensor encodes analyte information through multiple figures of merit, yet how electrostatic gating and carrier transport couple at the graphene–electrolyte interface remains unresolved. Here, stability-filtered polynomial analysis of three reduced graphene oxide GFET datasets (pH, Cl−, and HEV ORF2) is consistent with analyte-dependent coupling patterns across these three representative systems: ionic sensing—particularly pH—exhibits a stable, reproducible VCNP·gm,h interaction consistent with co-varying surface-potential shifts and mobility changes, whereas protein detection (ORF2) is characterized by transconductance–curvature cross terms consistent with Debye-screened scattering. Chloride sensing occupies an intermediate regime with weaker but reproducible VCNP-linked contributions within a curvature-dominant pattern. These explicit second-order coupling terms suggest that ionic-sensing behavior may be associated with electrostatic–transport coupling, which is potentially tunable through quantum-capacitance/double-layer engineering, while protein sensing appears to respond primarily through scattering channels accessible via functionalization design.