Microfluidic SERS devices: brightening the future of bioanalysis
Open Access
- 15 December 2022
- journal article
- review article
- Published by Springer Nature in Discover Materials
- Vol. 2 (1) , 1-50
Abstract
A new avenue has opened up for applications of surface-enhanced Raman spectroscopy (SERS) in the biomedical field, mainly due to the striking advantages offered by SERS tags. SERS tags provide indirect identification of analytes with rich and highly specific spectral fingerprint information, high sensitivity, and outstanding multiplexing potential, making them very useful in in vitro and in vivo assays. The recent and innovative advances in nanomaterial science, novel Raman reporters, and emerging bioconjugation protocols have helped develop ultra-bright SERS tags as powerful tools for multiplex SERS-based detection and diagnosis applications. Nevertheless, to translate SERS platforms to real-world problems, some challenges, especially for clinical applications, must be addressed. This review presents the current understanding of the factors influencing the quality of SERS tags and the strategies commonly employed to improve not only spectral quality but the specificity and reproducibility of the interaction of the analyte with the target ligand. It further explores some of the most common approaches which have emerged for coupling SERS with microfluidic technologies, for biomedical applications. The importance of understanding microfluidic production and characterisation to yield excellent device quality while ensuring high throughput production are emphasised and explored, after which, the challenges and approaches developed to fulfil the potential that SERS-based microfluidics have to offer are described.Keywords
Funding Information
- FCT - Fundação para a Ciência e a Tecnologia, I.P., (SFRH/BD/132057/2017, LA/P/0140/2020)
- FCT - Fundação para a Ciência e a Tecnologia, I.P. (UIDP/50025/2020, LA/P/0037/2020, UIDP/04378/2020)
- Fundação para a Ciência e a Tecnologia (UIDB/50025/2020)
- European Community H2020 program (No. 716510, ERC-2016-STG TREND)
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