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Record W2088304763 · doi:10.1063/1.481952

Can surface-enhanced Raman scattering serve as a channel for strong optical pumping?

2000· article· en· W2088304763 on OpenAlexafffund
T. L. Haslett, Li‐Lin Tay, Martin Moskovits

Bibliographic record

VenueThe Journal of Chemical Physics · 2000
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRaman spectroscopyRaman scatteringExcited stateCoherent anti-Stokes Raman spectroscopyResonance (particle physics)Molecular physicsPopulationLaserMaterials scienceChemistryMoleculeAtomic physicsOpticsPhysics

Abstract

fetched live from OpenAlex

The surface-enhanced Raman scattering spectra of a number of dye and colorless molecules adsorbed on deposited coloidal silver films were systematically studied as a function of power and position using a Raman microscope. The anti-Stokes portions of the spectra of the dyes reproducibly show line intensities much greater than what is expected on the basis of the equilibrium population of the excited vibrational states, even at the lowest incident light intensities used. This behavior was observed previously and attributed to optical pumping of vibrationally excited states of the molecules by unusually intense surface-enhanced Raman transitions, [Phys. Rev. Lett. 76, 2444 (1996)] suggesting either uncommonly large Raman cross-sections or very intense local field strengths exceeding those encountered in the most powerful currently available lasers. Based on this work, however, we ascribe the apparently large anti-Stokes intensities primarily to a difference in the Stokes and anti-Stokes Raman cross-sections resulting from resonance or pre-resonance Raman processes in the adsorbate–surface complex rather than to strongly nonequilibrium populations in the molecular vibrational states. Finally, we observed no significant inhomogeneity in the Raman enhancement in the images of the deposited silver coloid samples down to spatial resolutions of ∼1 μm.

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 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 score0.007
Threshold uncertainty score0.257

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 head0.019
GPT teacher head0.254
Teacher spread0.235 · 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 teacher head, 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

Citations99
Published2000
Admission routes2
Has abstractyes

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