Surface Plasmon Resonance and Reduced Graphene Oxide for Optical Ion Monitoring in Water: A Numerical Modeling

In this work, we analyze how the coupling prism governs the performance of reduced-graphene-oxide (rGO)-assisted surface plasmon resonance (SPR) sensors for trace heavy-metal detection in water. A Kretschmann multilayer at 633 nm with a fixed Cu/Si3N4/rGO stack (45.0/5.00/1.41 nm) is modeled by transfer-matrix methods while varying the prism material among CaF2, BK7, SiO2, and SF6. Performance optimization is carried out using angular sensitivity, full width at half maximum (FWHM), figure of merit (FoM), detection accuracy (DA), quality factor (QF), and a practical limit of detection (LoD). The analyte is represented by refractive-index typical of clean and contaminated water (n = 1.330 and 1.340). SF6 yields the narrowest angular resonances but compresses analyte-induced angle spacing; CaF2 provides larger analyte separations and consequently higher FoM and lower LoD under angle-encoded readout. The rGO interlayer enhances surface interaction across all prisms when co-tuned with the Cu and Si3N4 thicknesses. The sensitivity peaks around 310–320°·RIU−1 for CaF2. These results highlight the prism as a primary design variable in rGO-enhanced SPR sensing and position CaF2-coupled architectures as promising for compact water-quality monitoring.