pH-dependent rGO/Cu–Cu2O electrodes with a porous PVA/PEO film for high-sensitivity non-enzymatic glucose sensing: a COMSOL multiphysics study

Abstract

A comprehensive 2D finite-element model based on COMSOL Multiphysics has been developed to investigate the pH-dependent electrochemical performance of reduced graphene oxide/copper–cuprous oxide (rGO/Cu–Cu₂O) nanocomposite electrodes stabilised by a NaOH-treated porous polyvinyl alcohol/polyethylene oxide (PVA/PEO) film for non-enzymatic glucose detection in alkaline media (pH 9.12–14.09). The model couples the Nernst equation for open-circuit potential, Butler–Volmer kinetics for glucose oxidation via the Cu(II)/Cu(III) redox shuttle, Nernst–Planck transport for glucose and OH⁻, and charge conservation across the porous polymer layer. Optimal electrocatalytic activity is achieved at pH 13.03, delivering an ultrahigh sensitivity of 853.19 µA mM⁻¹ cm⁻², a stable open-circuit potential of 0.653 V (vs. Ag/AgCl), a linear range up to 10.2 mM, and a rapid response time of 2.08 s. Systematic parametric analysis reveals that decreasing PVA/PEO film thickness to ∼300 nm, reducing Cu–Cu₂O nanoparticle diameter below 30 nm, and increasing rGO conductivity above 1400 S m⁻¹ dramatically enhance both sensitivity and response speed by improving ion accessibility and electron-transfer efficiency. Model predictions are rigorously validated against experimental electrochemical impedance spectroscopy data (RMSE = 0.08), confirming predictive accuracy. The work elucidates fundamental pH–structure–performance relationships and provides quantitative design guidelines for robust, cost-effective, enzyme-free glucose sensors suitable for diabetes monitoring and wearable diagnostic platforms.