Arduino-based portable point-of-care colorimetric glucose biosensor using nanozyme with enhanced peroxidase-like activity

Nanozymes engineered to mimic natural enzyme catalysis have emerged as promising alternatives due to their enhanced stability, cost-effectiveness, and tunable catalytic properties compared to biological enzymes. Developing nanozymes with well-defined porous structures and heteroatom doping is key to improving catalytic efficiency and selectivity particularly for applications in biosensing. Nanotechnology has become a key enabler in advancing catalysis, biosensing, and environmental monitoring thanks to the exceptional properties of nanomaterials such as large surface area, customizable optical characteristics, and enhanced catalytic activity. In this study, a novel nanozyme platform based on creatinine–thiourea–FeCl₃ nanoparticles (CTF-NPs) was developed via a one-step pyrolysis method using colloidal silica as a porosity template. The synthesized CTF-NPs were uniformly structured as confirmed by SEM, EDX, FT-IR, UV–Vis, and XRD and featured effective nitrogen, sulfur, and iron doping contributing to their catalytic efficiency. The CTF-NPs exhibited strong peroxidase-like activity catalyzing the colorimetric oxidation of o-phenylenediamine (OPD) in the presence of hydrogen peroxide (H₂O₂). Kinetic studies revealed a K_m of 0.819 mM and a V_max of 1.620 μM/min outperforming several previously reported nanozyme systems. The sensor displayed a linear detection range of 10–700 μM for H₂O₂ with an excellent correlation coefficient (r= 0.9975) optimal at pH 4, 40 °C, and 10-minute incubation. Upon coupling with glucose oxidase (GOx), the platform enabled indirect glucose detection via enzymatically generated H₂O₂ showing a linear range of 100–600 μM with a correlation coefficient of r= 0.9953. The system exhibited high selectivity against common interferents, reproducible fabrication, and reliable performance in spiked human serum samples. Integration of the nanozyme system with a portable RGB color sensor (TCS34725) enabled quantitative, user-friendly, and instrument-free detection supporting the development of accessible point-of-care diagnostics. This work introduces a scalable and robust platform for glucose monitoring with promising implications for diabetes management and decentralized healthcare.