Optimization of photonic crystal fiber biosensor by particle swarm algorithm

Abstract

A hexagonal shape surface plasmon photonic crystal fiber (PCF) biosensor is reported and studied numerically. The proposed design has three identical cores along the y-axis filled with liquid (analyte). Additionally, the central core is coated by a gold layer to facilitate the coupling among the plasmonic modes and the core fundamental modes. A full vectorial finite element method is used to analyze the proposed sensor with a perfectly matched layer boundary condition. Further, the particle swarm optimization (PSO) technique is used to optimize and improve the sensitivity of the presented sensor as well as reduce the sensor’s size. Through the optimization process, the diameters of the three cores, and the thicknesses of the gold layer are fluctuated. For a wavelength range 1.46-1.47, the sensitivity of the proposed sensor is 4000 nm/RIU.