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Updated: Jul 3, 2025

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets

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Published on: March 17, 2023

Amplifying Sensing Capabilities: Combining Plasmonic Resonances and Fresnel Reflections through Multivariate

Jaione Etxebarria-Elezgarai¹, Luca Bergamini^2,3, Eneko Lopez^1,4

¹CIC nanoGUNE BRTA, Tolosa Hiribidea 76, San Sebastian, 20018, Spain.

|February 14, 2024

Summary

This summary is machine-generated.

This study enhances biosensing performance using gold nanodiscs and machine learning. The innovative approach significantly boosts analytical sensitivity and sensor resolution for improved detection.

Keywords:

fresnel reflections kretschmann configuration localized surface plasmons multivariate analysis partial least squares plasmonic nanostructures plasmonic surface lattice resonances

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Area of Science:

Nanotechnology
Biosensing
Optics

Background:

Multivariate analysis improves biosensing by extracting key information and mitigating noise.
Plasmonic sensors offer high sensitivity for detecting dielectric changes.

Purpose of the Study:

To enhance biosensing performance using gold nanodiscs as a metasurface in a Kretschmann setup.
To leverage machine learning and multivariate analysis for improved analytical sensitivity and resolution.

Main Methods:

Utilized gold nanodiscs as a metasurface in a Kretschmann configuration.
Employed machine learning to analyze features from the reflectance curve.
Integrated the metasurface with a microfluidic chamber to incorporate Fresnel reflections.

Main Results:

Engineered metasurface generated novel plasmonic features beyond classical Kretschmann resonance.
Integrated device provided additional spectral features from Fresnel reflections.
Multivariate analysis enhanced analytical sensitivity by over 200% and sensor resolution by 20%, reducing prediction errors by 40%.

Conclusions:

The combination of plasmonic metasurfaces and Fresnel reflections significantly improves biosensing capabilities.
This approach offers enhanced detection performance applicable to commonly available setups.