‘When is a hotspot a good nanospot’: review of analytical and hotspot-dominated surface enhanced Raman spectroscopy nanoplatforms

Mike Hardy*, Pola Goldberg Oppenheimer*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

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Abstract

Substrate development in surface-enhanced Raman spectroscopy (SERS) continues to attract research interest. In order to determine performance metrics, researchers in foundational SERS studies use a variety of experimental means to characterize the nature of substrates. However, often this process would appear to be performed indiscriminately without consideration for the physical scale of the enhancement phenomena. Herein, we differentiate between SERS substrates whose primary enhancing structures are on the hundreds of nanometer scale (analytical SERS nanosubstrates) and those whose main mechanism derives from nanometric-sized gaps (hot-spot dominated SERS substrates), assessing the utility of various characterization methods for each substrate class. In this context, characterization approaches in white-light spectroscopy, electron beam methods, and scanning probe spectroscopies are reviewed. Tip-enhanced Raman spectroscopy, wavelength-scanned SERS studies, and the impact of surface hydrophobicity are also discussed. Conclusions are thus drawn on the applicability of each characterization technique regarding amenability for SERS experiments that have features at different length scales. For instance, while white light spectroscopy can provide an indication of the plasmon resonances associated with 10 s–100 s nm-scale structures, it may not reveal information about finer surface texturing on the true nm-scale, critical for SERS’ sensitivity, and in need of investigation via scanning probe techniques.
Original languageEnglish
Pages (from-to)3293-3323
Number of pages31
JournalNanoscale
Volume16
Early online date17 Jan 2024
DOIs
Publication statusE-pub ahead of print - 17 Jan 2024

Bibliographical note

Acknowledgements
We acknowledge funding from the Wellcome Trust (174ISSFPP) and the EPSRC (EP/V029983/1). We also acknowledge the funding by UK Research and Innovation (UKRI) under the UK Government's Horizon Europe Funding Guarantee (ERC Consolidator Grant, EP/Y030206/1). This review is the result of many discussions with colleagues over the years for which we are grateful. Colleagues at the School of Maths and Physics, Queen's University Belfast, Drs Paul Dawson, Ryan McCarron, Matt Doherty and many numerical modeling discussions with Dr James Bennington. Conversations on SERS work with Professor Steven Bell and Dr Taifur Rahman, School of Chemistry and Chemical Engineering, Queen's University Belfast, especially in hydrophobic theory, and Dr Wayne Dickson, Department of Physics, King's College London, were all appreciated. We are also thankful to Lucie Marešová, Department of Physical Electronics, Czech Technical University in Prague, for introducing correlative SEM-Raman (RISE) as well as colleagues, Dr Hin On Martin Chu and Dr Paulo de Carvalho Gomes, School of Chemical Engineering, University of Birmingham, for discussions on SERS in general and numerical modelling and machine learning, respectively.

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