An analytical revision of the bio-functional layer/electrolyte interface and modelling of dynamic signal transduction in two-dimensional BioFETs.

Authors

Chishu Homma, Matthias Stadler, Dibyendu Khan, Nagesh Samane, Sven Ingebrandt, Yuhei Hayamizu, Vivek Pachauri

Published in

Nanoscale. Jul 14, 2026. Epub Jul 14, 2026.

Abstract

Graphene-based biologically sensitive field-effect transistors (BioFETs) are promising electrical biosensors owing to their two-dimensional (2D) transducer channels that are exceptionally sensitive to the interfacial phenomena. The signal transduction in such 2D BioFETs often originates via mechanisms that are beyond surface charge sensitivity and not fully captured by conventional models. Here, we present an analytical framework for reduced graphene oxide (rGO)-based 2D BioFETs that integrates a drift-diffusion description of electrical transport with solid-liquid interface physics via a two-dimensional/bio-functional layer/electrolyte interface (2DiBLE) model. The approach treats the electrical double layer (EDL) and the bio-functional layer (BFL) as dynamic series capacitances including the binding-induced dielectric modulation of the BFL and interfacial water. In this novel analytical framework, the charge carrier densities in the 2D channel are expressed in closed form as functions of BFL thickness, effective permittivity and binding occupancy, enabling predictions of transfer characteristics and minimum conductivity. Simulations based on this framework validate key experimental findings from aptamer-ligand binding including thickness-dependent current changes, polarity and magnitude of charge-neutral-point shifts, and decreases in minimum conductivity due to enhanced scattering under reduced permittivity. The model quantitatively obeys the dose-response curves measured and resolves apparent discrepancies between affinities inferred from voltage shifts and conductivity metrics through distinct sensitivity kernels. By explicitly coupling electrostatics, dielectric effects, and transport in rGO channels, the 2DiBLE framework provides a compact yet predictive tool for interpreting 2D BioFET sensor signals and for rationally optimizing interfacial architecture.

PMID:
42446898
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.

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