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Record W4221029608 · doi:10.5541/ijot.1000945

Revisiting The Phase Diagram of Au – Cu Alloy at Nanoscales

2022· article· en· W4221029608 on OpenAlexaff
Fatemeh MONJİ, Mohammad Amin Jabbareh

Bibliographic record

VenueInternational Journal of Thermodynamics · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicnanoparticles nucleation surface interactions
Canadian institutionsYork University
Fundersnot available
KeywordsLiquidusPhase diagramCALPHADSolidusMaterials scienceAlloyThermodynamicsPhase (matter)DiagramParticle (ecology)Particle sizeWork (physics)NanoparticleMetallurgyNanotechnologyChemistryPhysical chemistryMathematicsPhysicsGeology

Abstract

fetched live from OpenAlex

Au – Cu nanoparticles are widely used as catalysts in different chemical reactions. Since knowing the phase diagram of nano-alloys is crucial for effective design of nano-catalysts, there have been many efforts to predict the size effect on the phase diagram of the Au – Cu system. However, reported results are inconsistent and sometimes contradictory. In this work, a CALPHAD type thermodynamic model was applied to recalculate the phase diagram of Au – Cu binary alloy nanoparticles at different sizes. The results show that decreasing particle size decreases liquidus and solidus temperatures as well as the congruent melting point. It was also found that by reduction of the particle size, the composition of the congruent alloy shifts towards the Au – rich side of the phase diagram.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.276
Teacher spread0.260 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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