Synergistic Integration of Reduced Graphene Oxide and Molecularly Imprinted Polymer on an Interdigital Electrode for Real-Time and Ultra-Trace Detection of Melamine
摘要
Melamine (MEL), a nitrogen-rich compound illicitly added to milk and dairy products to falsify protein content, poses severe health hazards, including nephrotoxicity, renal failure, and infant mortality. In this study, a rationally designed reduced graphene oxide-poly(methacrylic acid-co-ethylene glycol dimethacrylate) hybrid film immobilized on an interdigital electrode is presented for the development of a high-sensitivity electrochemical sensor for MEL detection. Density functional theory calculations identified methacrylic acid as the most favorable functional monomer and dimethyl sulfoxide as the optimal porogenic solvent, ensuring stable pre-polymerization complex formation with MEL. The successful synthesis of the imprinted matrix and complete template removal were confirmed by Fourier-transform infrared spectroscopy and ultraviolet–visible spectroscopy, respectively, while surface morphology was characterized using scanning electron microscopy and atomic force microscopy, revealing a porous and uniformly imprinted topology. The fabricated reduced graphene oxide (rGO)-molecularly imprinted polymer (MIP)-based interdigital electrode sensor exhibited an excellent linear sensor response toward MEL concentrations ranging from 1 to 90 ppm (R2 = 0.9908), achieving a limit of detection of 30 ppb and a limit of quantification of 129 ppb, outperforming conventional MIP sensors by nearly an order of magnitude. The synergistic combination of rGO and MIP significantly enhanced electron transfer kinetics and binding-site accessibility, resulting in superior sensitivity, selectivity, and stability compared to non-imprinted controls. The sensor demonstrated remarkable reproducibility (relative standard deviation <3%), reusability, and long-term stability, underscoring its potential for rapid, on-site, and real-time monitoring of MEL contamination in complex food matrices.