Work

Design and modelling of a plus-shaped cavity SPR sensor for RI-based detection of human sperm samples

Year: 2025

Type: article

Abstract: The optical fiber grating sensors utilize periodic structures to detect refractive index (RI) variations, enabling highly sensitive, compatible, and compact footprints for various analytical setups. However, optical detection of human sperm cells remains challenging due to their complex and non-uniform structure. The non-uniformity of sperm cells disrupts the light patterns required for grating-based analysis, causing high variability and reducing sensitivity. To address this, a Plus-Shaped Cavity (PSC) optical sensor is developed, integrating gold (Au), cerium oxide (CeO 2 ), and graphene oxide (GO) layers for RI-based detection of human sperm samples based on their concentration and mobility. The Au layer facilitates surface plasmon resonance (SPR), an optical effect that arises when polarized light interacts with a thin metal film at the interface between two media of different RIs. CeO 2 enhances the sensor's compatibility with targeted analytes and is synthesized using a combustion process , ensuring stable and reliable synthesis. Transmission electron microscopy (TEM) provides the insights into the morphological characteristics of the synthesized CeO 2 . The GO layer further improves the sensor’s biocompatibility. Human sperm sample concentrations and mobility, ranging from 17 to 197 million/ml and 41 to 81, respectively, are used as analytes for the proposed sensor. The work involves measuring the output power using two-dimensional Finite Difference Time Domain (FDTD) simulations along with COMSOL Multiphysics analysis. The results demonstrate that the sensor exhibits a notable sensitivity of 669.72 nm/RIU, accompanied by an autocorrelation coefficient R 2 = 1. However, the autocorrelation coefficient after the decimal points is settled around R 2 = 0.47. The significant results and easy fabrication make the proposed scheme a potential candidate for detecting biological samples.

Source: Next research.

DOI: 10.1016/j.nexres.2025.100351