Evidence map›Paper›PMID 35062554›Full record

ArticleSensors (Basel, Switzerland)2022

Power Spectral Density Analysis for Optimizing SERS Structures.

Ekaterina Babich, Sergey Scherbak, Ekaterina Lubyankina, Valentina Zhurikhina, Andrey Lipovskii

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ekaterina BabichLaboratory of Multifunctional Glassy Materials, World-Class Research Center "Advanced Digital Technologies", Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, 195251 St. Petersburg, Russia.ORCID 0000-0003-4970-2591
Sergey ScherbakLaboratory of Multifunctional Glassy Materials, World-Class Research Center "Advanced Digital Technologies", Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, 195251 St. Petersburg, Russia.
Ekaterina LubyankinaLaboratory of Optics of Heterogeneous Structures and Optical Materials, Alferov University, Khlopina 8/3, 194021 St. Petersburg, Russia.
Valentina ZhurikhinaLaboratory of Multifunctional Glassy Materials, World-Class Research Center "Advanced Digital Technologies", Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, 195251 St. Petersburg, Russia.ORCID 0000-0003-0685-9409
Andrey LipovskiiLaboratory of Multifunctional Glassy Materials, World-Class Research Center "Advanced Digital Technologies", Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya 29, 195251 St. Petersburg, Russia.ORCID 0000-0001-9472-9190

Funding

Ministry of Science and Higher Education of the Russian Federation World-class Research Center program: Advanced Digital Technologies (contract No. 075-15-2020-934 dated 17.11.2020)
6 · The paper itself

Abstract

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.

Indexed as

metal nanostructurespower spectral densitysurface enhanced Raman scattering

Identifiers

PMID35062554
PMCPMC8778882

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.