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Power Spectral Density Analysis for Optimizing SERS Structures

The problem of optimizing the topography of metal structures allowing Surface Enhanced Raman Scattering (SERS) sensing is considered. We developed a model, which randomly distributes hemispheroidal particles over a given area of the glass substrate and estimates SERS capabilities of the obtained str...

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Detalles Bibliográficos
Autores principales: Babich, Ekaterina, Scherbak, Sergey, Lubyankina, Ekaterina, Zhurikhina, Valentina, Lipovskii, Andrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778882/
https://www.ncbi.nlm.nih.gov/pubmed/35062554
http://dx.doi.org/10.3390/s22020593
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author Babich, Ekaterina
Scherbak, Sergey
Lubyankina, Ekaterina
Zhurikhina, Valentina
Lipovskii, Andrey
author_facet Babich, Ekaterina
Scherbak, Sergey
Lubyankina, Ekaterina
Zhurikhina, Valentina
Lipovskii, Andrey
author_sort Babich, Ekaterina
collection PubMed
description The problem of optimizing the topography of metal structures allowing Surface Enhanced Raman Scattering (SERS) sensing is considered. We developed a model, which randomly distributes hemispheroidal particles over a given area of the glass substrate and estimates SERS capabilities of the obtained structures. We applied Power Spectral Density (PSD) analysis to modeled structures and to atomic force microscope images widely used in SERS metal island films and metal dendrites. The comparison of measured and calculated SERS signals from differing characteristics structures with the results of PSD analysis of these structures has shown that this approach allows simple identification and choosing a structure topography, which is capable of providing the maximal enhancement of Raman signal within a given set of structures of the same type placed on the substrate.
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spelling pubmed-87788822022-01-22 Power Spectral Density Analysis for Optimizing SERS Structures Babich, Ekaterina Scherbak, Sergey Lubyankina, Ekaterina Zhurikhina, Valentina Lipovskii, Andrey Sensors (Basel) Article The problem of optimizing the topography of metal structures allowing Surface Enhanced Raman Scattering (SERS) sensing is considered. We developed a model, which randomly distributes hemispheroidal particles over a given area of the glass substrate and estimates SERS capabilities of the obtained structures. We applied Power Spectral Density (PSD) analysis to modeled structures and to atomic force microscope images widely used in SERS metal island films and metal dendrites. The comparison of measured and calculated SERS signals from differing characteristics structures with the results of PSD analysis of these structures has shown that this approach allows simple identification and choosing a structure topography, which is capable of providing the maximal enhancement of Raman signal within a given set of structures of the same type placed on the substrate. MDPI 2022-01-13 /pmc/articles/PMC8778882/ /pubmed/35062554 http://dx.doi.org/10.3390/s22020593 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Babich, Ekaterina
Scherbak, Sergey
Lubyankina, Ekaterina
Zhurikhina, Valentina
Lipovskii, Andrey
Power Spectral Density Analysis for Optimizing SERS Structures
title Power Spectral Density Analysis for Optimizing SERS Structures
title_full Power Spectral Density Analysis for Optimizing SERS Structures
title_fullStr Power Spectral Density Analysis for Optimizing SERS Structures
title_full_unstemmed Power Spectral Density Analysis for Optimizing SERS Structures
title_short Power Spectral Density Analysis for Optimizing SERS Structures
title_sort power spectral density analysis for optimizing sers structures
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778882/
https://www.ncbi.nlm.nih.gov/pubmed/35062554
http://dx.doi.org/10.3390/s22020593
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