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  5. Chitosan Micro-Membranes with Integrated Gold Nanoparticles as an LSPR-Based Sensing Platform

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Article
en
2022

Chitosan Micro-Membranes with Integrated Gold Nanoparticles as an LSPR-Based Sensing Platform

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en
2022
Vol 12 (11)
Vol. 12
DOI: 10.3390/bios12110951

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Rui L Reis
Rui L Reis

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Diana I. Meira
Manuela Proença
Rita Rebelo
+6 more

Abstract

Currently, there is an increasing need to develop highly sensitive plasmonic sensors able to provide good biocompatibility, flexibility, and optical stability to detect low levels of analytes in biological media. In this study, gold nanoparticles (Au NPs) were dispersed into chitosan membranes by spin coating. It has been demonstrated that these membranes are particularly stable and can be successfully employed as versatile plasmonic platforms for molecular sensing. The optical response of the chitosan/Au NPs interfaces and their capability to sense the medium's refractive index (RI) changes, either in a liquid or gas media, were investigated by high-resolution localized surface plasmon resonance (HR-LSPR) spectroscopy, as a proof of concept for biosensing applications. The results revealed that the lowest polymer concentration (chitosan (0.5%)/Au-NPs membrane) presented the most suitable plasmonic response. An LSPR band redshift was observed as the RI of the surrounding media was incremented, resulting in a sensitivity value of 28 ± 1 nm/RIU. Furthermore, the plasmonic membrane showed an outstanding performance when tested in gaseous atmospheres, being capable of distinguishing inert gases with only a 10-5 RI unit difference. The potential of chitosan/Au-NPs membranes was confirmed for application in LSPR-based sensing applications, despite the fact that further materials optimization should be performed to enhance sensitivity.

How to cite this publication

Diana I. Meira, Manuela Proença, Rita Rebelo, Ana I. Barbosa, Marco S. Rodrigues, Joel Borges, F. Vaz, Rui L Reis, Vítor M. Correlo (2022). Chitosan Micro-Membranes with Integrated Gold Nanoparticles as an LSPR-Based Sensing Platform. , 12(11), DOI: https://doi.org/10.3390/bios12110951.

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Publication Details

Type

Article

Year

2022

Authors

9

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.3390/bios12110951

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