Adsorption-driven Graphene Oxide SPR Biointerfaces: Coupled Thermodynamic, Kinetic, and Optical Modeling with...

Area of Science:

• Biophysics
• Materials Science
• Nanotechnology

Background:

• Surface Plasmon Resonance (SPR) biosensors are crucial for label-free biomolecular detection.
• Graphene Oxide (GO) functionalization enhances SPR sensitivity and stability.
• Theoretical modeling is needed to optimize GO-SPR biointerface performance.

Purpose of the Study:

• To develop a theoretical framework for adsorption-driven GO-functionalized SPR biointerfaces.
• To link molecular adsorption parameters (concentration, kinetics, thermodynamics) to SPR optical response.
• To optimize GO-SPR sensor design and predict performance metrics.

Main Methods:

• Coupling transfer-matrix optical modeling with generalized Langmuir-Hill adsorption formalism.
• Simulating angular interrogation at 633 nm for a prism/TiW/Au/GO multilayer structure.
• Incorporating temperature dependence via van't Hoff treatment and time-dependence via first-order kinetics.

Main Results:

• Optimized effective thicknesses for Au, TiW, and GO layers were identified.
• Model predicts resonance shifts, effective biolayer thickness, and refractive-index sensitivity.
• Estimated limit of detection is ~0.027 μM with optimal angular resolution, dependent on angular noise.

Conclusions:

• The developed framework provides a mechanism-aware computational tool for GO-SPR biointerfaces.
• It connects adsorption thermodynamics and kinetics to SPR optical signals.
• The model highlights effective-parameter limits and guides experimental validation for biosensor development.