Mechanistic understanding of electrochemical nitrogen reduction reaction on hybrid plasmonic nanostructures using operando surface-enhanced Raman spectroscopy

AbstractThe fabrication of plasmonic nanostructures with a reliable, low cost and easy approach has become a crucial and urgent challenge in many fields, including surface-enhanced Raman spectroscopy (SERS) based applications. In this frame, nanoporous metal films are quite attractive, due to their intrinsic large surface area and high density of metal nanogaps, acting as hot-spots for Raman signal enhancement. In this paper, we report a detailed study on the fabrication of nanoporous silver-based SERS substrates, obtained by the application of two successive treatments with an Inductively Coupled Plasma (ICP) system, using synthetic air and Ar as feeding gases. The obtained substrates exhibit a quite broad plasmonic response, covering the Vis–NIR range, and an enhancement factor reaching 6.5 $$\times\, 10^7$$ × 10 7 , estimated by using 4-mercaptobenzoic acid (4-MBA) as probe molecule at 532 nm. Moreover, the substrates exhibit a quite good spatial reproducibility on a centimeter scale, which assures a good signal stability for analytical measurements. Globally, the developed protocol is easy and cost effective, potentially usable also for mass production thanks to the remarkable inter-batches reproducibility. As such, it holds promise for its use in SERS-based sensing platforms for sensitive detection of targets molecules.

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Evaluating Adhesion Layers for Plasmonic Nanostructures with Monochromated STEM-EELS and Surface Enhanced Raman Spectroscopy

Microscopy and Microanalysis ◽

10.1017/s1431927615011058 ◽

2015 ◽

Vol 21 (S3) ◽

pp. 2055-2056 ◽

Cited By ~ 1

Author(s):

Steven J Madsen ◽

Ai Leen Koh ◽

Robert Sinclair

Keyword(s):

Raman Spectroscopy ◽

Surface Enhanced Raman Spectroscopy ◽

Plasmonic Nanostructures ◽

Surface Enhanced ◽

Surface Enhanced Raman

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Rationally designed multifunctional plasmonic nanostructures for surface-enhanced Raman spectroscopy: a review

Reports on Progress in Physics ◽

10.1088/0034-4885/77/11/116502 ◽

2014 ◽

Vol 77 (11) ◽

pp. 116502 ◽

Cited By ~ 54

Author(s):

Wei Xie ◽

Sebastian Schlücker

Keyword(s):

Raman Spectroscopy ◽

Surface Enhanced Raman Spectroscopy ◽

Plasmonic Nanostructures ◽

Surface Enhanced ◽

Surface Enhanced Raman

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Design and Fabrication of Plasmonic Nanostructures with DNA for Surface-Enhanced Raman Spectroscopy Applications

Chinese Journal of Chemistry ◽

10.1002/cjoc.201500806 ◽

2016 ◽

Vol 34 (3) ◽

pp. 273-282 ◽

Cited By ~ 2

Author(s):

Chunbo Leng ◽

Cheng Wang ◽

Huixin Xiu ◽

Xiangmeng Qu ◽

Lizhen Chen ◽

...

Keyword(s):

Raman Spectroscopy ◽

Surface Enhanced Raman Spectroscopy ◽

Plasmonic Nanostructures ◽

Surface Enhanced ◽

Surface Enhanced Raman

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Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies

Molecules ◽

10.3390/molecules25215209 ◽

2020 ◽

Vol 25 (21) ◽

pp. 5209

Author(s):

Hyunku Shin ◽

Dongkwon Seo ◽

Yeonho Choi

Keyword(s):

Raman Spectroscopy ◽

Free Surface ◽

Signal Analysis ◽

Surface Enhanced Raman Spectroscopy ◽

Pattern Identification ◽

Plasmonic Nanostructures ◽

Label Free ◽

Surface Enhanced ◽

Analysis Strategies ◽

Surface Enhanced Raman

Extracellular vesicles (EVs) have been widely investigated as promising biomarkers for the liquid biopsy of diseases, owing to their countless roles in biological systems. Furthermore, with the notable progress of exosome research, the use of label-free surface-enhanced Raman spectroscopy (SERS) to identify and distinguish disease-related EVs has emerged. Even in the absence of specific markers for disease-related EVs, label-free SERS enables the identification of unique patterns of disease-related EVs through their molecular fingerprints. In this review, we describe label-free SERS approaches for disease-related EV pattern identification in terms of substrate design and signal analysis strategies. We first describe the general characteristics of EVs and their SERS signals. We then present recent works on applied plasmonic nanostructures to sensitively detect EVs and notable methods to interpret complex spectral data. This review also discusses current challenges and future prospects of label-free SERS-based disease-related EV pattern identification.

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