Novel Optimization Approach and AI Performance Prediction of a Highly Sensitive V-Shaped PCF-SPR Sensor for Cancer Cell DetectionFor cancer cell detection, we present in this paper a novel optimized photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) biosensor. The sensor features a V-shaped groove, which enhances sensitivity by improving electromagnetic coupling between the surface plasmon mode (SPM) and the core mode at the metal/dielectric interface. Key design parameters, including the diameter of the small air hole (d2), V-channel depth (h), and gold layer thickness (tg), are optimized through the Box-Behnken Design (BBD) method, reaching a maximum spectral sensitivity of 2142.86 nm/RIU for blood and breast cancer cells, an amplitude sensitivity of 632.50 RIU⁻¹ for skin cancer cells, and a resolution of 4.66 ℅ 10− 5 RIU. Furthermore, we employed an artificial neural network (ANN) model based on a Multi-Layer Perceptron (MLP) to accurately predict sensor performance, demonstrating the potential of machine learning in optimizing biosensor applications for biochemical and biological detection
|
10
[Other]Optimized circular arrays for enhanced near-field beamforming in 6G wireless systems
