Surface plasmon resonance (SPR) sensors are extensively employed for label-free, real-time monitoring of subtle refractive index variations at metal-dielectric interfaces, making them highly effective platforms for chemical and biochemical sensing. In this study, a numerically validated multilayer surface plasmon resonance (SPR) refractive index sensor is proposed composed of a silver (Ag) plasmonic layer integrated with methylammonium lead halide perovskite (MAPbX 3 ) and the low-dimensional material hafnium diselenide (HfSe 2 ) on a BK7 prism substrate. The hybrid heterostructure combines the excellent plasmonic characteristics of Ag, the variable optical absorption of MAPbX 3 , as well as the very high carrier mobility, and anisotropic optical characteristics of HfSe 2 to create greater confinement of the electromagnetic fields at the sensor interface. Electromagnetic modeling using the transfer matrix method and finite element simulations in COMSOL Multiphysics enabled optimization of layer thicknesses and evaluation of angular sensitivity, figure of merit (FOM), and detection limit. The Optimal Configuration is Ag: 56 nm; MAPbX 3 : 2.0 nm; HfSe 2 : 3.0 nm. This configuration provides an extremely high angular sensitivity of 320 ° /RIU at a wavelength of 633 nm. A strong linear relationship exists between resonance angle and refractive index variation within the range of 1.334 - 1.355 RIU (R 2 = 0.988). Machine learning models were employed to optimize computational efficiency and enable rapid prediction of sensor response, while maintaining a high level of accuracy (achieving an R 2 > 0.99). Electric field analysis confirms a maximum field strength of approximately 2.5 × 10 5 V/m when the angle of resonance is 76.6 ° as evidence of the strong plasmonic coupling in the multi-layer structure. Overall, the proposed design based on a perovskite-HfSe 2 heterostructure represents an adaptable, physics-based, high-sensitivity refractive index sensing platform for future chemically or biologically functionalized sensing applications.
Kumar et al. (Wed,) studied this question.
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