Ultra-high-sensitive SPR device composed of CaF2 prism, Ag, graphene, and sensing medium for refractive index detection-artificial neural network training

Abstract

The current work focuses on a refractive index (RI) biosensor using prism configuration used for various sensing applications. This design is suggested for evaluating the intensities of the reflectance for visible and near infrared wavelength range at fixed incident direction (=80 degree). Different materials used to realize our biosensor, the CaF₂ prism, the silver (Ag), and the graphene. A numerical method based on the electromagnetic theory is employed to compute the reflectance property. Significant results concerning the sensitivity and reflection depth are showed after optimizing some geometrical parameters. The parameters used to examine the biosensor’s performance are the RI sensitivity (S_RI), figure of merit (FoM), and quality factor (QF). The higher values of S_RI, FoM, and QF provided by our suggested structure are 54600 nm/RIU, 151 /RIU^‐1, and 6.29 respectively, when the RI is ranging from 1.33 to 1.39. In this research, for input parameters of our sensor, we predict the sensitivity’s data by using the artificial neural network technique. It is remarked that the latest approach shows a significant results compared to that obtained by the theoretical method. In the context of temperature sensing, our device showed an average temperature sensitivity of 6.99 nm/K, and a maximum, sensitivity of 17.68 nm/K.