Photonic Crystal Fiber-Based Plasmonic Biosensor for Cancer Cell Detection
摘要
A highly sensitive surface plasmon resonance (SPR)-based photonic crystal fiber (PCF) sensor is proposed for advanced biosensing applications. Designed to precisely distinguish the sensitivity peaks of different analytes, the sensor’s performance has been extensively evaluated using COMSOL Multiphysics software with the finite volume finite element method (FVFEM). Noble metals such as gold, silver, tin, and nickel are employed for SPR excitation due to their excellent chemical stability and inertness. To further enhance the SPR effect, the integration of graphene and other 2D nanomaterials has been explored. These materials offer remarkable electrical, optical, and surface properties, including high surface area and strong light–matter interactions, making them ideal for improving sensor sensitivity and selectivity. Recent studies also highlight the growing importance of 2D nanomaterials in enhancing SPR-based biosensing, particularly in biomedical applications. In this study, silver and tin were selected along with silica, and their sensor responses were compared. The sensor features symmetrically placed air holes and an analyte space in the outer region for easy sample injection. Simulation results indicate that the tin-based design performs best within a refractive index range of 1.33 to 1.38, while the silver-based design is optimal between 1.35 and 1.4. Both designs achieve a wavelength sensitivity of 5000 nm/RIU for X-polarization core mode with a resolution of 2 × 10−6 RIU. The maximum amplitude sensitivity recorded was 1313.47 RIU−1 for silver and 1130 RIU−1 for tin. Biocompatible plasmonic sensors are gaining attention due to their potential in biomedical detection, including proteins, DNA, and cancer markers. The proposed sensor is designed with future applications in mind, particularly for cancer cell detection and monitoring disease progression. In the future, such biosensors could enable real-time monitoring of cancer stages, improving early diagnosis and treatment strategies.