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Record W1598129346 · doi:10.1063/1.4921127

On the importance of collective excitations for thermal transport in graphene

2015· article· en· W1598129346 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueApplied Physics Letters · 2015
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversité de MontréalRegroupement Québécois sur les Matériaux de Pointe
FundersFonds de recherche du Québec – Nature et technologiesCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsGrapheneQuasiparticleCondensed matter physicsPhononHeat fluxConductorMolecular dynamicsPhysicsRelaxation (psychology)Lattice (music)ThermalThermal conductivityMaterials scienceHeat transferSuperconductivityQuantum mechanicsThermodynamics

Abstract

fetched live from OpenAlex

We use equilibrium molecular dynamics (MD) simulations to study heat transport in bulk single-layer graphene. Through a modal analysis of the MD trajectories employing a time-domain formulation, we find that collective excitations involving flexural acoustic (ZA) phonons, which have been neglected in the previous MD studies, actually dominate the heat flow, generating as much as 78% of the flux. These collective excitations are, however, much less significant if the atomic displacements are constrained in the lattice plane. Although relaxation is slow, we find graphene to be a regular (non-anomalous) heat conductor for sample sizes of order 40 μm and more.

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 score0.017
Threshold uncertainty score0.319

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 head0.034
GPT teacher head0.236
Teacher spread0.202 · 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