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Record W3025858871 · doi:10.1021/acs.jpcc.0c04095

Thermal Conductivity of High-Temperature Phases of Cu<sub>2</sub>S from <i>Ab Initio</i> Molecular Dynamics: Advent of Lattice-Site Hopping

2020· article· en· W3025858871 on OpenAlexafffund
Xue Yong, Niall J. English, John S. Tse

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2020
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Thermoelectric Materials and Devices
Canadian institutionsUniversity of SaskatchewanUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermal conductivityThermoelectric materialsAb initioCondensed matter physicsLattice (music)Thermoelectric effectThermodynamicsMaterials scienceThermalMolecular dynamicsChemical physicsAb initio quantum chemistry methodsElectrical resistivity and conductivityChemistryPhysicsComputational chemistryMolecule

Abstract

fetched live from OpenAlex

The nontoxic, earth-abundant compound copper sulfide is fascinating in its thermal and putative quasi-diffusive behavior, especially in its high-temperature phases (above ambient temperature). Indeed, gauging its possible promising thermoelectric performance is an important endeavor for a variety of industrial and geophysical applications. Here, we apply state-of-the-art ab initio molecular dynamics with the Einstein approach to evaluate the thermal conductivity of two higher temperature phases at 450 and 700 K, obtaining a semiquantitative agreement with experiment, especially when considering the nature of the powder sample Cu2S and its nondirect thermal conductivity estimation. We also discover that the apparent quasi-diffusive behavior conjectured previously for Cu2S in its phase at circa 700 K arises in fact from lattice-site hopping, belying notions of its liquid nature.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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