Optimization Of Surface Charge Density For Measuring Stability In A Cortisol Sensor Using Nanomaterials With Comsol Multiphysics

Abstract

Abstract: Cortisol is a vital stress-associated hormone. An efficient technology that provides cortisol detection is important for stress management and wearable devices. While nanomaterial-based electrochemical biosensors offer quick response times and have demonstrated excellent sensitivity, they face long-term performance issues due to charge transfer instability at the electrode surface. In this paper, we used COMSOL Multiphysics to perform comparative numerical analyses of graphene, zinc oxide (ZnO), and carbon nanotube (CNT) cortisol electrochemical biosensors. A two-dimensional axisymmetric geometry integrated electroanalytical modelling with Butler-Volmer electrode kinetics to evaluate responses in current density and surface charge density across different electrodes. From the results, we show that surface charge density and electrochemical current output are strongly related, suggesting that surface charge density is a determinant of performance. Among the three materials, graphene had the highest surface charge density, yielding the most stable response. In comparison, both ZnO and CNTs had lower levels of charge accumulation. The results support the idea that surface charge density not only improves sensitivity but also offers a more meaningful measure of the electrochemical cortisol biosensor. The findings of this study are useful for the development of wearable and point-of-care electrochemical cortisol biosensors by optimizing surface charge density