Experimentally Driven Numerical Model of Carbon/Polyaniline-Based Glucose Monitoring Sensors: An Evaluation Using a New Figure of Merit

This study presents an experimentally driven numerical model for evaluating carbon/polyaniline (PANI)-based glucose monitoring sensors (GMSs), focusing on innovative configurations using graphene-PANI and carbon nanotube (CNT)-PANI composites. We performed a thorough analysis of the morphological, electrophysical, and electrical properties of these materials, ultimately leading to the extraction of key electrical parameters for integration into a finite element model (FEM). This model simulates the entire sensor, enabling the estimation of critical performance metrics such as sensitivity, limit of detection (LOD), linearity, and power consumption. Our findings demonstrate that the CNT-PANI configuration significantly outperforms the laser-induced graphene (LIG)-PANI electrode, achieving a figure of merit (FOM) of 0.99 compared to 0.62, thanks to its superior electrical conductivity and high surface area, which facilitates enhanced charge transfer and electrochemical reactions. The optimized sensor configurations reveal optimal parameters for LIG-PANI and CNT-PANI, underscoring the tradeoffs between conductivity and overall sensor performance. Notably, the CNT-PANI composite exhibits the highest sensitivity of $2778~\mu $ A $\cdot $ $\text{mM}^{-{1}} \cdot $ $cm^{-{2}}$ and the lowest LOD of $0.09~\mu $ M, making it a promising candidate for glucose detection in clinical applications. This work highlights the importance of power consumption in sensor design, with all configurations operating at 0.232 mW, and sets a new benchmark for future glucose monitoring technologies. Finally, the study illustrated a clinical investigation to verify the selectivity and sensitivity of PANI toward various molar concentrations of glucose.