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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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.998

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 teacher head, not a consensus.

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

Citations1
Published2022
Admission routes1
Has abstractyes

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