Smartphone-based colorimetric glucose biosensor using peroxidase-like activity of bimetallic catalyst supported onto...

Portable analytical platforms are rapidly transforming point-of-care chemical analysis by enabling fast, on-site measurements with minimal instrumentation, reduced cost, and simplified operation. Among emerging approaches, smartphone-assisted sensing systems have attracted considerable attention due to their accessibility, integrated imaging capabilities, and potential for quantitative analysis without sophisticated laboratory equipment. In this study, a smartphone-based colorimetric sensing platform is developed for sensitive and selective glucose determination using bimetallic cobalt-nickel co-modified graphitic carbon nitride (Co-Ni/g-C₃N₄) nanoparticles as efficient peroxidase-mimicking nanozymes. The Co-Ni/g-C₃N₄ nanocomposite was synthesized through a hydrothermal-assisted reduction method and characterized by SEM, HRTEM, EDX, FTIR, and XRD, confirming successful incorporation of Co and Ni within the g-C₃N₄ structure. The sensing strategy relies on an enzyme-nanozyme cascade reaction in which glucose oxidase converts glucose to gluconic acid, producing hydrogen peroxide that is subsequently utilized by the Co-Ni/g-C₃N₄ nanozyme to catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine, generating a blue color signal proportional to glucose concentration. The color intensity was recorded using a smartphone camera and quantitatively analyzed through RGB extraction with ImageJ software. Under optimized conditions, the platform exhibited linear detection ranges of 10-500 µM (UV-Vis) and 10-300 µM (smartphone analysis) along with low detection limits, high sensitivity, and excellent selectivity toward glucose against common interferents. The smartphone-based measurements showed strong agreement with conventional UV-Vis results, demonstrating the reliability of the portable approach. This simple and cost-effective sensing system highlights the potential of integrating bimetallic g-C₃N₄ nanozymes with smartphone colorimetry for decentralized glucose monitoring and point-of-care biochemical analysis.