A portable sensor for glucose detection in Huangshui based on blossom-shaped bimetallic organic framework loaded with silver nanoparticles combined with machine learning

In this work, we propose a blossom-like Ni, Co bimetallic metal-organic framework (NiCo-MOF) synthesized hydrothermally and decorated with silver nanoparticles (AgNPs) via chemical reduction for electrochemical enzyme-free glucose sensing. The NiCo-MOF nanostructures had large specific surface area and good sensing performance. The AgNPs enhanced the electrochemical performance of the MOF, resulting in excellent electrochemical activity. The sensor exhibited sensitivities of 1191.84 and 271.19 μA mM-1 cm-2 in the linear ranges of 0.005-1.125 and 1.525-5.325 mM, respectively, with a detection limit of 2.3 μM. The sensor was successfully applied for glucose determination in Huangshui (HS) using an artificial neural network as machine learning (ML) model. The R2 value near 1, low RMSE, and high RPD values of the proposed ML model demonstrate its excellent fitting and prediction performance. This will provide a fast and portable intelligent sensing analysis technology for the detection of glucose in HS.