Modeling and Numerical Simulation of an Immobilized Enzyme Conductometric Urea Biosensor

Abstract

In this study, a mathematical model for predicting the response of a conductometric urea biosensor was developed and numerically simulated. The biosensor features a planar interdigitated electrode array with immobilized urease. The enzymatic hydrolysis of urea generates ionic products, such as ammonium (NH₄⁺) and bicarbonate (HCO3-) ions, altering the solution's electrical conductivity. To optimize the biosensor performance, key physicochemical processes were analyzed through numerical modeling and validated against experimental data, showing strong agreement. Simulations under varying conditions supported the experimental design, improved the analytical performance, and reduced the development costs. While previous studies have explored conductometric urea biosensors, few have addressed optimizations through numerical modeling. This study addresses this gap by examining the effects of temperature, pH, enzyme layer thickness, and CO2 concentration using the COMSOL Multiphysics software. The model accurately predicted conductivity variations across different urea concentrations, with optimal responses being observed at 37 °C, 5% CO2, pH 7.4, and an enzymatic zone length of 500 µm. These results offer valuable insights for enhancing the design and application of conductometric urea biosensors in biomedical and environmental fields.