Numerical Analysis of Electrochemical Biosensing of Catecholamine Neurotransmitter

Abstract The detection of catecholamines such as dopamine, epinephrine, and norepinephrine plays a vital role in diagnosing and monitoring neurological disorders such as Parkinson's disease, Alzheimer's disease, and epilepsy. Electrochemical biosensors provide real‐time, highly sensitive, and cost‐effective solutions for catecholamine detection, particularly when enhanced with nanostructures and functionalized electrode surfaces. Here a 3D double‐layer microelectrode (DLME) model developed through high‐fidelity numerical simulations is present to analyse cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) responses. The model incorporates ion‐electron conduction, double‐layer capacitance, and redox reactions at the electrode–electrolyte interface in both PBS and blood samples. Simulation results demonstrate anodic peak potentials near 142 mV, with current responses ranging from picoamperes to 100 nA, enabling the detection at picomolar levels. The redox peak currents scale linearly with the square root of scan rate, confirming diffusion‐controlled electrochemical behavior, while EIS spectra provide insights into charge transfer resistance and electrode kinetics. Functionalized electrode surfaces further enhance the sensitivity, selectivity, and stability, allowing the device to discriminate catecholamines from other neurotransmitters at nanomolar concentrations. These results highlight the potential of simulation‐guided electrochemical biosensor design for advancing next‐generation neurochemical diagnostics.