Abstract

We present a simulation-guided design for a multilayer surface plasmon resonance (SPR)-based biosensor that can detect changes in the refractive index of a target induced by analytes. Surface plasmons are excited through a hybrid Kretschmann configuration with a low-refractive-index calcium fluoride (CaF₂) prism under transverse magnetic polarization illumination. In the sensing architecture, the copper (Cu) layer is a plasmonic metal, overlaid with a thin nickel (Ni) layer that protects it from oxidation. To improve analyte coupling and electromagnetic confinement, a dielectric layer of barium titanium oxide (BaTiO₃) and a monolayer of graphene oxide (GO) are used. The layer structure is iteratively optimized employing the transfer matrix method for angular interrogation at a wavelength of 1064 nm, focusing on key performance metrics including sensitivity, minimum reflectivity, and figure of merit (FOM). The finite element method-based simulation confirms SP excitation through consistent and optimal performance of individual layer thicknesses with Cu thickness of 30 nm and BaTiO₃ thickness of 5 nm. The SPR-based sensor (CaF₂-Cu-Ni-BTO-GO) is designed and has achieved a sensitivity of 157.8°/RIU and an FOM of 17.48 RIU-1 while detecting the presence of the E. Coli bacterium in the water, indicative of the biosensor's application.

Abstract

We present a simulation-guided design for a multilayer surface plasmon resonance (SPR)-based biosensor that can detect changes in the refractive index of a target induced by analytes. Surface plasmons are excited through a hybrid Kretschmann configuration with a low-refractive-index calcium fluoride (CaF₂) prism under transverse magnetic polarization illumination. In the sensing architecture, the copper (Cu) layer is a plasmonic metal, overlaid with a thin nickel (Ni) layer that protects it from oxidation. To improve analyte coupling and electromagnetic confinement, a dielectric layer of barium titanium oxide (BaTiO₃) and a monolayer of graphene oxide (GO) are used. The layer structure is iteratively optimized employing the transfer matrix method for angular interrogation at a wavelength of 1064 nm, focusing on key performance metrics including sensitivity, minimum reflectivity, and figure of merit (FOM). The finite element method-based simulation confirms SP excitation through consistent and optimal performance of individual layer thicknesses with Cu thickness of 30 nm and BaTiO₃ thickness of 5 nm. The SPR-based sensor (CaF₂-Cu-Ni-BTO-GO) is designed and has achieved a sensitivity of 157.8°/RIU and an FOM of 17.48 RIU-1 while detecting the presence of the E. Coli bacterium in the water, indicative of the biosensor's application.

Abstract

We present a simulation-guided design for a multilayer surface plasmon resonance (SPR)-based biosensor that can detect changes in the refractive index of a target induced by analytes. Surface plasmons are excited through a hybrid Kretschmann configuration with a low-refractive-index calcium fluoride (CaF₂) prism under transverse magnetic polarization illumination. In the sensing architecture, the copper (Cu) layer is a plasmonic metal, overlaid with a thin nickel (Ni) layer that protects it from oxidation. To improve analyte coupling and electromagnetic confinement, a dielectric layer of barium titanium oxide (BaTiO₃) and a monolayer of graphene oxide (GO) are used. The layer structure is iteratively optimized employing the transfer matrix method for angular interrogation at a wavelength of 1064 nm, focusing on key performance metrics including sensitivity, minimum reflectivity, and figure of merit (FOM). The finite element method-based simulation confirms SP excitation through consistent and optimal performance of individual layer thicknesses with Cu thickness of 30 nm and BaTiO₃ thickness of 5 nm. The SPR-based sensor (CaF₂-Cu-Ni-BTO-GO) is designed and has achieved a sensitivity of 157.8°/RIU and an FOM of 17.48 RIU-1 while detecting the presence of the E. Coli bacterium in the water, indicative of the biosensor's application.

Abstract

We present a simulation-guided design for a multilayer surface plasmon resonance (SPR)-based biosensor that can detect changes in the refractive index of a target induced by analytes. Surface plasmons are excited through a hybrid Kretschmann configuration with a low-refractive-index calcium fluoride (CaF₂) prism under transverse magnetic polarization illumination. In the sensing architecture, the copper (Cu) layer is a plasmonic metal, overlaid with a thin nickel (Ni) layer that protects it from oxidation. To improve analyte coupling and electromagnetic confinement, a dielectric layer of barium titanium oxide (BaTiO₃) and a monolayer of graphene oxide (GO) are used. The layer structure is iteratively optimized employing the transfer matrix method for angular interrogation at a wavelength of 1064 nm, focusing on key performance metrics including sensitivity, minimum reflectivity, and figure of merit (FOM). The finite element method-based simulation confirms SP excitation through consistent and optimal performance of individual layer thicknesses with Cu thickness of 30 nm and BaTiO₃ thickness of 5 nm. The SPR-based sensor (CaF₂-Cu-Ni-BTO-GO) is designed and has achieved a sensitivity of 157.8°/RIU and an FOM of 17.48 RIU-1 while detecting the presence of the E. Coli bacterium in the water, indicative of the biosensor's application.