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Record W2900583794 · doi:10.25071/10315/35375

Thermal Conductivity Of Beta-Arsenene Under Biaxial Tensile Strain: A First Principle Study

2018· article· en· W2900583794 on OpenAlexafffund
Armin Taheri, Carlos Da Silva, Cristina H. Amon

Bibliographic record

VenueProgress in Canadian Mechanical Engineering · 2018
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoGovernment of OntarioCompute Canada
KeywordsBETA (programming language)Thermal conductivityMaterials scienceStrain (injury)ConductivityTensile strainUltimate tensile strengthCondensed matter physicsComposite materialPhysicsComputer scienceQuantum mechanicsMedicine

Abstract

fetched live from OpenAlex

A first principle study is conducted to explore the phonon thermal transport in a buckled arsenene monolayer (-As) subjected to tensile strain. The results showed that the thermal conductivity first decreases with strains from 0% to 1%, then it increases with strains from 1% to 5%, and finally it decreases with strains from 5% to 9%. The maximum thermal conductivity occurs at strain of 5%, which is 1.45 times higher than that of unstrained arsenene. Phonon properties are investigated to understand the causes of this thermal response to strain.

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 categoriesInsufficient payload (model declined to judge)
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 score0.044
Threshold uncertainty score1.000

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)0.0010.000

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 head0.265
Teacher spread0.231 · 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.

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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

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