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Models and Equations for Atomic Transport Coefficients of Liquid Metals: Viscosity and Self-Diffusivity

2007· article· en· W1971701307 on OpenAlexaff
Takamichi Iida, Nagendra Tripathi, M. Isac, Rod I.L. Guthrie

Bibliographic record

VenueMaterials science forum · 2007
Typearticle
Languageen
FieldEngineering
TopicThermodynamic and Structural Properties of Metals and Alloys
Canadian institutionsMcGill University
Fundersnot available
KeywordsThermal diffusivityMelting pointThermodynamicsSurface tensionViscosityMaterials scienceLiquid metalMetalAluminiumSelf-diffusionMagnesiumPhysicsMetallurgyComposite material

Abstract

fetched live from OpenAlex

The current article presented appropriate models using a new parameter recently introduced by the authors to accurately predict the atomic transport coefficients, i.e. viscosity and self-diffusivity, of liquid metallic elements at their melting points. The models for both the meltingpoint viscosity and self-diffusivity are expressed in terms of well-known physical quantities; atomic mass, atomic volume, melting point, melting-point surface tension, and the new parameter T ξ . Moreover, the authors derived expressions for the temperature dependence of the atomic transport coefficients of liquid metallic elements in terms of melting point temperature. These two models give very good agreement with experimental data for various metallic liquids. Using the models, self-diffusivities were predicted for liquid aluminum, calcium, and magnesium.

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 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 score0.196
Threshold uncertainty score0.300

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)0.0000.000

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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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

Citations12
Published2007
Admission routes1
Has abstractyes

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