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Record W2104352698 · doi:10.1073/pnas.0803748105

Probing atomic ordering and multiple twinning in metal nanocrystals through their vibrations

2008· article· en· W2104352698 on OpenAlexaff
Hervé Portalès, Nicolas Goubet, Lucien Saviot, S. V. Adichtchev, D. B. Murray, A. Mermet, E. Duval, M. P. Piléni

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2008
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsCrystallinityRaman spectroscopyNanocrystalCrystal twinningMaterials scienceAnisotropyRaman scatteringVibrationMolecular vibrationChemical physicsCondensed matter physicsMolecular physicsNanotechnologyOpticsChemistryPhysicsAcousticsComposite material

Abstract

fetched live from OpenAlex

Control of nanocrystal (NC) crystallinity currently raises great interest because of its potential benefits in both physics modeling and technological applications. Advances in methods for synthesizing perfect single-crystalline NCs are recent, so that the effect of crystallinity on NC properties has received only limited study and still needs to be properly investigated. Here, we report that crystallinity of gold NCs dramatically modifies their vibrations. Using low-frequency Raman scattering, we clearly demonstrate that single-domain NCs vibrate differently than their multiply twinned counterparts, through the splitting of the quadrupolar vibrations, which is only observed for the former. Using the resonant ultrasound approach, we calculate the vibrational frequencies of a gold sphere and show that elastic anisotropy induces a lift of degeneracy of the quadrupolar mode in good agreement with our experimental measurements. These findings open up challenging perspectives on using Raman spectroscopy to characterize nanocrystallinity.

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 score0.020
Threshold uncertainty score0.256

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 studies0.0000.001
Scholarly communication0.0000.001
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 head0.060
GPT teacher head0.277
Teacher spread0.218 · 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

Citations100
Published2008
Admission routes1
Has abstractyes

Explore more

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