Framework enhances sensitivity in multi-point surface plasmon resonance sensing, suggesting advancements in biomedical applications.
Surface plasmon resonance (SPR) enables real‐time, label‐free detection of biomolecular interactions, but traditional intensity‐based methods suffer from limited sensitivity due to noise and environmental fluctuations. Phase‐sensitive SPR methods provide significant sensitivity and signal‐to‐noise ratio improvements by measuring phase variations in reflected light, however, current systems rely on relatively complex interferometry, making them prone to misalignment and environmental drift. Neural networks have been explored for phase retrieval and have shown some potential. However, they often require large datasets or lack generalization and precision. This work presents a framework for robust, alignment‐tolerant phase retrieved high‐sensitivity high‐throughput SPR sensing. By integrating an objective lens‐based coupling system with a rotation‐based ePIE (r‐ePIE) phase retrieval on the back focal planes, the method reduces beam distortion and significantly enhances spatial resolution over prism‐based setups. System aberration is accurately reconstructed and calibrated with the algorithm. Experiments demonstrate accurate recovery of complex phase patterns, including high‐order optical vortices, and thus enabling high‐precision multi‐point SPR sensing with minimal crosstalk. Reconstructed resonance shifts and sample thicknesses agree well with measured data. The state‐of‐the‐art throughput spacing of has been experimentally demonstrated, showing strong promise for sensitive, high‐throughput SPR sensing in biochemical and biomedical applications.
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Shen et al. (2025) studied this question.
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