A Numerical Study of Dual Core Surface Plasmon Resonance-based Photonic Crystal Fiber Biosensors.
Abstract
Photonic crystals (PCs) are periodic material structures in the optical domain. Felix Bloch developed a theory that describes how electron waves behave in the periodic structure of solids such as semiconductors. The same theory can be applied in an optical domain, and it can explain how photons or light waves behave in periodic crystals. In essence, photonic crystals are artificial materials structured to possess a periodic modulation of refractive index so that the structure influences the propagation and confinement of light within it. Several researchers have demonstrated PCs' exceptional properties in the domain of photonic-crystal-fibers (PCF)-based surface-plasmon-resonance (SPR) biosensors. Recently, numerous designs have been created that have exceptional sensing performance. There is often a tradeoff between sensitivity and confinement loss of these sensors. To reduce this tradeoff, we achieved greater sensitivity while incurring a few losses by creating two distinct sensor designs: unique, susceptible, and easy to fabricate. The analysis of both sensors has been conducted using the finite element method based on COMSOL Multiphysics software. Structural design and theoretical modeling have been done for proposed designs 1 and 2, SPR-based PCF biosensors. The designs have been optimized by varying several parameters, such as the thickness of plasmonic material, air hole diameter, analyte layer thickness, pitch variation, and perfectly matched layer variation. The corresponding confinement losses were also calculated. Mode analysis was performed, and the physics-controlled mesh was used in FEM-based software. Both prototypes have a particular arrangement of air holes within the fiber, resulting in exceptional sensing capabilities. Proposed design 1 is a dual-core PCF with a wide sensing range of refractive index (RI) from 1.21 to 1.40. Maximum amplitude sensitivity of 1096〖RIU〗^(-1), wavelength sensitivity of 7000nm/RIU, and maximum sensor resolution of 5×10^(-5) have been achieved, respectively. A diverse array of biomolecules can be detected using this design. This biosensor was further analyzed to identify three types of cancer cells: basal, Jurkat, and MCF-7. Confinement losses, resonant conditions, and wavelength shifts were examined. The numerical analysis showed that the maximum sensitivity achieved was 878〖RIU〗^(-1) for the skin's basal cells. Proposed design 2 is a plasmonic RI sensor for detecting low RI using a sensitive dual-core PCF. Maximum amplitude sensitivity of 393〖RIU〗^(-1), wavelength sensitivity of 12000nm/RIU, and resolution of 8.33×10^(-6) have been obtained, respectively. Plasmonic material, silver, was applied externally to the fiber structure to monitor variations in the RI of the surrounding medium.