Multiphysics insights into flow-assisted electrochemical sensing of niclosamide: effects of surface fouling and regeneration

Abstract

A comprehensive multiphysics modeling framework is developed to elucidate flow-assisted electrochemical sensing of niclosamide in microfluidic systems employing palygorskite-carbon nanocomposite-modified electrodes. The model integrates laminar fluid flow, convection–diffusion mass transport, Butler–Volmer electrochemical kinetics, and Langmuir-type surface fouling within a finite-element platform. Simulations were performed over volumetric flow rates of 0.1–10 µL min⁻¹ and niclosamide concentrations of 0.01–10 µM, revealing that increasing flow rate significantly enhances mass transfer and reduces the response time to reach 90% of the steady-state signal (t_90%) from 60.0 ± 2.8 s to 21.4 ± 1.1 s, corresponding to a 64% decrease. Simultaneously, the steady-state electrochemical current increases from 15.95 ± 0.72 µA to 38.98 ± 1.56 µA (n = 5, RSD < 5%). Sensitivity improves from 15.19 ± 0.68 to 19.80 ± 0.82 µA µM⁻¹. Long-term simulations over a 30 day operation period predict progressive surface fouling, with the fractional surface coverage rising to 0.78 and the normalized current decaying to 22% of its initial value. A systematic evaluation of regeneration strategies demonstrates that electrochemical voltage pulsing restores up to 95% of the original signal, outperforming solvent washing and ultrasonic cleaning. The proposed model shows excellent agreement with experimental data, yielding a root mean square error of 0.069. Overall, this study develops a quantitative multiphysics modeling framework to analyze the coupled roles of hydrodynamics, electrochemical kinetics, and surface fouling in flow-assisted niclosamide sensing.