@misc{10481/111880,
year = {2026},
month = {3},
url = {https://hdl.handle.net/10481/111880},
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.},
organization = {European Union’s Horizon 2020 - (No. 101155159)},
organization = {MICIU/AEI/10.13039/501100011033 and by FSE+ - (JDC2023-052442-I)},
organization = {R+D+i co-financed by the Consejería de Universidad, Investigación e Innovación and the European Union under the FEDER Andalucía 2021–2027 - (project A-ING-253-UGR23 AMBITIONS)},
publisher = {Elsevier},
keywords = {Graphene},
keywords = {Biosensor},
keywords = {Field-effect transistor},
title = {General modeling of graphene field-effect biosensors: Application to label-free DNA hybridization detection},
doi = {10.1016/j.biosx.2026.100764},
author = {El Grour, Tarek and García Ruiz, Francisco Javier and Assis Dias, Felipe de and González Marín, Enrique and Godoy Medina, Andrés and Pasadas Cantos, Francisco},
}