Model-Driven Discovery of Highly Sensitive Nanocolumnar NiO Electrochemical Glucose Sensors

Abstract

Nanostructured NiO electrodes fabricated using glancing angle deposition (GLAD) are promising platforms for nonenzymatic electrochemical glucose sensing, owing to their high surface area and tunable morphology. With GLAD, adjusting the deposition angle and substrate rotation rate can significantly affect electrochemical performance; however, identifying optimal GLAD structures for specific use cases is still largely experimental, relying on trial and error. Here, we develop a multiscale modeling framework that links the GLAD film growth process to glucose electro-oxidation performance by combining on-lattice kinetic Monte Carlo (kMC) simulations with morphology characterization and a coupled reaction–diffusion electrochemical model. Key morphological features, including surface area, porosity, and directional tortuosities, are quantified from kMC-generated structures across a wide range of GLAD geometries, such as slanted posts, helical shapes, and vertical nanocolumns. These features are then incorporated into a homogenized porous electrode model for glucose electro-oxidation on Ni-based catalysts. The model clarifies how the trade-off between surface area and mass transport governs electrode sensitivity. We identify a slanted-post morphology deposited at 72.5° as the optimal design for maximizing glucose electro-oxidation, and we find that physical electrodes formed with similar geometries were approximately 25% more sensitive to glucose than those formed with the vertical post morphology previously considered to be the optimum (i.e., 1.38 mA/mM·cm² vs 1.12 mA/mM·cm²). Beyond glucose, this modeling workflow provides general guidelines for designing GLAD-fabricated electrodes for other biosensing targets and for electrochemical applications, including energy conversion and hydrogen generation.