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◆ PLoS ONE2025-11-07· Materials science

Enhanced surface plasmon resonance biosensor with graphene-black phosphorus heterostructure for ultra-high sensitivity refractive index detection with machine learning for behaviour prediction

Jacob Wekalao, Hussein A. Elsayed, Ahmed Mehaney, Amuthakkannan Rajakannu, Haifa A. Alqhtani, May Bin‐Jumah, Jonas Muheki, Stefano Bellucci

原始摘要(英文原文)· Original abstract
This study reports a five-layer surface plasmon resonance biosensor architecture comprising a BK7 glass substrate, silver plasmonic film, monolayer graphene, black phosphorus dielectric, and analyte region, engineered for high-precision detection of low refractive index media. The graphene-black phosphorus heterostructure synergistically exploits the exceptionally high surface-to-volume ratio of graphene and the anisotropic optical response of black phosphorus, enabling pronounced electromagnetic field confinement at the sensor interface. In particular, the detection procedure is mainly dependent on the emergence of the angular surface plasmon resonance based on the optimum values of the different geometrical and structural parameters. Therefore, the electromagnetic optimization using COMSOL Multiphysics was performed by varying the silver thickness, graphene thickness and black phosphorus thickness over an analyte index range of 1.29-1.38 RIU. The optimized configuration achieved a maximum sensitivity of 300°/RIU at n = 1.35 RIU, with a figure of merit of 45.455 RIU-1 and a detection limit of 0.018 RIU, surpassing previously reported architectures. Furthermore, predictive validation employing K-nearest neighbours regression demonstrated excellent reliability, yielding R² values between 92-100% and mean absolute errors of 0.005-0.012 RIU.
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Enhanced surface plasmon resonance biosensor with graphene-black phosphorus heterostructure for ultra-high sensitivity refractive index detection with machine learning for behaviour prediction — 科研速览 Science Skim