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Record W2416394136 · doi:10.1021/acs.jpcc.6b02400

Single-Molecule Surface-Enhanced (Resonance) Raman Scattering (SE(R)RS) as a Probe for Metal Colloid Aggregation State

2016· article· en· W2416394136 on OpenAlexafffund
Diego P. dos Santos, Márcia L. A. Temperini, Alexandre G. Brolo

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2016
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversidade Estadual de CampinasFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsSurface plasmon resonanceRaman scatteringResonance (particle physics)Raman spectroscopyChemistryScatteringMoleculeColloidElectric fieldCharacterization (materials science)Molecular physicsAnalytical Chemistry (journal)Chemical physicsMaterials scienceNanoparticleNanotechnologyAtomic physicsPhysical chemistryOpticsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

Single-molecule surface-enhanced (resonance) Raman scattering (SM-SE(R)RS) studies have applications beyond analytical chemistry. For instance, SM-SERS spectra carry information about the molecule interaction with the hotspots (regions of strong electric field enhancement due to surface plasmon resonance). The analysis of the time- (or spatial-) dependent fluctuations in SM-SERS spectra permits, for instance, the study of resonance contributions from the local electric field to imbalances in the anti-Stokes to Stokes intensity ratios ( I AS / I S ). This analysis is a tool for the characterization of the resonance energies of the hotspots. In the case of colloidal samples, the structures of the hotspots and their properties are dependent upon the colloidal aggregation state. The analysis of the I AS / I S ratios in such a system can be a useful characterization tool to infer the hotspot structures for different aggregation states. In this work, the distributions of I AS / I S ratio for crystal violet (CV) adsorbed in Ag colloids at different aggregation states was studied under SM-SERS conditions. The experimental results were interpreted in terms of the generalized Mie theory (GMT) simulations.

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 score0.002
Threshold uncertainty score0.234

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 head0.016
GPT teacher head0.253
Teacher spread0.237 · 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

Citations33
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry CSame topicGold and Silver Nanoparticles Synthesis and ApplicationsFrench-language works237,207