MétaCan
Menu
Back to cohort
Record W2128856790 · doi:10.1021/jp3010597

Side-by-Side Assembly of Gold Nanorods Reduces Ensemble-Averaged SERS Intensity

2012· article· en· W2128856790 on OpenAlexafffund
Anna Lee, Aftab Ahmed, Diego P. dos Santos, Neil Coombs, Jai Il Park, Reuven Gordon, Alexandre G. Brolo, Eugenia Kumacheva

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2012
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of VictoriaUniversity of Toronto
FundersDivision of Materials ResearchNatural Sciences and Engineering Research Council of Canada
KeywordsNanorodPlasmonMaterials scienceColloidal goldNanoparticleRaman scatteringCluster (spacecraft)Electric fieldRaman spectroscopyNanotechnologySurface-enhanced Raman spectroscopyPlasmonic nanoparticlesOptoelectronicsChemical physicsOpticsChemistryPhysicsComputer science

Abstract

fetched live from OpenAlex

It is generally expected that aggregates of metal nanoparticles are more efficient surface-enhanced Raman scattering (SERS) probes than individual nanoparticles, due to the enhancement of the electric field in the interparticle gaps. We show that, for asymmetric nanoparticles, such as gold nanorods (NRs), this is not always the case: the plasmonic behavior of NRs depends on the mutual orientation of the NRs in the ensemble. We report the results of experimental studies and theoretical analysis of the optical properties of clusters of side-by-side assembled gold NRs. Ensemble-averaged SERS spectroscopy showed a reduction in SERS intensity. Comprehensive finite-difference time-domain simulations showed a reduction of electric field intensity as the number of NRs per cluster increased. This is due to destructive interference as the radial component of the surface plasmon modes of the NRs in the cluster interact with each other. The present work expands our understanding of the configuration-specific optical behavior of asymmetric gold nanoparticles. Furthermore, it offers guidance toward the “design rules” for the development of colloidal NR systems for sensing applications.

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)0.001
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 score0.001
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.249
Teacher spread0.233 · 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

Citations80
Published2012
Admission routes2
Has abstractyes

Explore more

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