A π-Configuration Plasmonic Dual Surface Plasmon Resonance Fiber Optic Sensor for Multi-Analyte Detection

Although optical fiber-based surface plasmon resonance (SPR) sensors have revolutionized real-time, label-free biosensing, conventional designs suffer from limited multi-analyte detection capabilities. This study utilizes the novel Pi (π)-configured dual SPR optical fiber sensor with two opposing side-polished surfaces, enabling plasmonic excitation for simultaneous multi-analyte detection. The proposed sensor leverages asymmetric metallic thin films such as Ag, Au, Cu, and hybrid configurations (metal + TiO₂) to generate two distinct resonance peaks, significantly enhancing detection versatility. Numerical simulations using the finite element method in COMSOL Multiphysics v6.3 demonstrate that the π-configuration achieves dual resonance dips at 982 nm and 1276 nm for Ag and Ag-TiO₂ films, 1040 nm and 1317 nm for Au and Au-TiO₂ films, and 977 nm and 1249 nm for Cu and Cu-TiO₂ films, respectively, for an analyte refractive index of 1.42. A peak spectral separation >125 nm was achieved for all the sensors for a refractive index range of 1.37-1.42, ensuring that the two dips are resolvable since the change in SPR wavelength is greater than or equal to the full width at half maximum, preserving dual-analyte capability and minimizing potential crosstalk. The results indicate that the π-configured dual SPR sensor utilizing silver and silver-TiO₂ sensing layers had the highest wavelength sensitivity of 12,600 nmRIU^-1 and 20,000 nmRIU^-1, respectively, slightly outperforming its gold and copper counterpart. The optimized metallic and hybrid nanostructured films ensure dual distinct peaks with high sensitivity, while maximizing refractive index resolution. This work presents the design of a π-configured SPR-based optical fiber sensor utilizing dielectric and multi-metallic thin films, thereby offering a breakthrough in multiplexed biosensing for applications in medical diagnostics, environmental monitoring, and chemical detection.