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Record W1822665022 · doi:10.1139/cjp-2015-0126

Nanoscale modeling of conduction heat transfer in metals using the two-temperature model

2015· article· en· W1822665022 on OpenAlexvenueno aff
Amir Reza Ansari Dezfoli, Z. Adabavazeh

Bibliographic record

VenueCanadian Journal of Physics · 2015
Typearticle
Languageen
FieldEngineering
TopicThermal Radiation and Cooling Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsThermal conductionElectronExcited stateLattice (music)Heat transferMetastabilityPhononMolecular dynamicsRelaxation (psychology)Condensed matter physicsAtomic physicsThermodynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

The goal of this study is to investigate the energy transfer in metals due to electron–phonon (lattice) interaction using the two-temperature model (TTM). In TTM, molecular dynamics simulation and classical energy equation are used to find the lattice and electronic temperatures, respectively. An initial temperature profile is considered for the electronic temperature. Then, the electronic and lattice temperatures are determined until they reach equilibrium. This means that we excite electrons with assignment an initial temperature profile and simulate the subsequent energy relaxation process. To study the phase change during simulation, the radial coordinate numbers of atoms are calculated. The results show that the excited electrons may act as a heat bath and transport energy to other parts of the lattice. The same approach can be used to gain a high level understanding in very fast heat transfer phenomena especially in laser–metal interaction.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.205

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 head0.050
GPT teacher head0.238
Teacher spread0.189 · 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 designSimulation or modeling
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

Citations2
Published2015
Admission routes1
Has abstractyes

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