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Record W2029296769 · doi:10.1080/09500340.2013.821535

Surface-enhanced Raman and optical scattering in coupled plasmonic nanoclusters

2013· article· en· W2029296769 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Modern Optics · 2013
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsNanoclustersRaman scatteringMaterials scienceExcitationPlasmonRaman spectroscopyScatteringElectric fieldWavelengthNanoparticleSurface plasmonElectromagnetic fieldMoleculeMolecular physicsOptoelectronicsNanotechnologyOpticsPhysics

Abstract

fetched live from OpenAlex

Optical excitation of small Au nanoparticle (NP) clusters of appropriate wavelength is known to generate intense electromagnetic fields localized uniquely at NP junction sites within the nanoclusters. These intense and localized field hot-sites can induce intense surface-enhanced Raman scattering (SERS) of molecules residing at the junction hot-sites. In this paper, we present a series of electromagnetic simulations, experimental SERS and extinction data obtained from small self-assembled Au NP clusters coated to saturation with a Raman reporter molecule. Our experimental data show that the SERS enhancement factor remains relatively constant despite the heterogeneity of the nanocluster and this is supported by the simulation results. Furthermore, our simulation results show significant variations in the localized electric field intensities of the junction hot-sites in different nanocluster geometries. This explains the observation that increasing the number of hot-sites does not necessarily result in a higher SERS enhancement factor.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.102
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.234
Teacher spread0.219 · 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