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Record W2064128192 · doi:10.1117/12.2040466

Substrate-induced effects on the plasmonic properties of strongly coupled silver nanocubes

2014· article· en· W2064128192 on OpenAlexafffund
Daniel Prezgot, Anatoli Ianoul

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceRaman spectroscopyMonolayerPlasmonSubstrate (aquarium)Refractive indexSurface-enhanced Raman spectroscopyOptoelectronicsSiliconSpectroscopyRaman scatteringNanotechnologyOptics

Abstract

fetched live from OpenAlex

The behaviour of the plasmonic modes of supported strongly coupled silver nanocubes is studied. Silver nanocube monolayers with controlled particle density were fabricated via the Langmuir-Blodgett technique and deposited on substrates with varying refractive indices. Substrates include glass, thin films of silicon, and titanium oxide on glass. The dipolar and bonded dipolar modes are red shifted with increasing refractive index of the substrate. Surface-enhanced Raman spectroscopy (SERS) is used as a tool to probe the electric field enhancements of the silver nanocube monolayers. SERS enhancement of silver nanocube monolayers is found to be highly substrate dependant, typically decreasing with increasing refractive index of the underlying substrate. This work aims to find the source of this enhancement decrease, and distinguishes between effects related electromagnetic enhancement and effects caused by the optics of the Raman spectroscopy system itself.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.211
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2014
Admission routes2
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicGold and Silver Nanoparticles Synthesis and ApplicationsFrench-language works237,207