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Record W2162254845 · doi:10.1016/j.crme.2011.03.009

From ballistic to diffusive regimes in heat transport at nano-scales

2011· article· en· W2162254845 on OpenAlexaff
G. Lebon, Miroslav Grmela, Charles Dubois

Bibliographic record

VenueComptes Rendus Mécanique · 2011
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPhononBallistic conductionScatteringHeat equationPhysicsConvection–diffusion equationStatistical physicsTransient (computer programming)MechanicsCondensed matter physicsQuantum mechanicsComputer science

Abstract

fetched live from OpenAlex

Our purpose is to model heat transport at micro- and nano-scales. At these scales, the mechanism of transport is not only diffusive, i.e. dominated by multiple scattering of phonons, but includes also a ballistic contribution due to collisions of phonons with the boundaries. To takes these effects into account, we follow the line of thoughts of Extended Irreversible Thermodynamics. The original idea underlying the present paper is to assume the coexistence of two kinds of heat carriers, namely ballistic and diffusive phonons, which are obeying different time-evolution equations: the diffusive collisions are described by a Cattaneo equation and ballistic interactions by a Guyer–Krumhansl like equation. The model is applied to the problem of transient heat transport in microfilms and the results are compared with earlier descriptions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.233
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2011
Admission routes1
Has abstractyes

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