| Download | - View supplementary information: Surface-enhanced Raman scattering substrate evaluation through intensity fluctuations (PDF, 3.3 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1021/acs.jpcc.5c01734 |
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| Author | Search for: Azarakhshi, Arash; Search for: Tay, Li-Lin1ORCID identifier: https://orcid.org/0000-0003-3408-3636; Search for: Brolo, Alexandre G.ORCID identifier: https://orcid.org/0000-0002-3162-0881 |
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| Affiliation | - National Research Council Canada. Metrology Research Centre
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| Format | Text, Article |
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| Subject | computer simulations; mathematical methods; molecular interactions; molecules; Raman spectroscopy |
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| Abstract | Surface-enhanced Raman scattering (SERS) has been established as a crucial technology for both qualitative and quantitative analyses. The application of SERS in analytical chemistry has prompted the development of various chemical and physical methods to produce reliable substrates. However, the field still faces a challenge related to the absence of standardized techniques and protocols to quantify and compare SERS substrates, fabricated using different approaches. Typically, the average enhancement factor (EF) parameter is determined and used for substrate evaluation. However, experimental challenges can introduce large uncertainty in the determination of EFs, and a more comprehensive approach that takes into consideration the various sources of variations in SERS is desirable for comprehensive characterization of substrates. SERS intensity fluctuations (SIFs) are observed when a SERS-active surface is exposed to a dye solution at very low concentrations. We demonstrated that the analysis of temporal SIFs for a fixed concentration (10 nM) of a molecular probe (Nile blue A) can provide parameters related to the enhancement characteristics of the SERS-active surface. Metrics related to the EF density of hotspots (HSs) and its distribution features were employed to parametrize the temporal fluctuations of the signal. A fundamental SERS signal simulation was performed to correlate the statistical signal analysis of the experimental data with a new set of metrics for substrate evaluation. |
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| Publication date | 2025-06-16 |
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| Publisher | American Chemical Society |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 3ffffc38-4355-446b-8369-fd94922b4197 |
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| Record created | 2026-02-04 |
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| Record modified | 2026-02-10 |
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