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Record W4393345724 · doi:10.53063/synsint.2024.41192

Solid-solution phase formation rules for high entropy alloys: A thermodynamic perspective

2024· article· en· W4393345724 on OpenAlexvenueno aff
Samaneh Mamnooni, Ehsan Borhani, Hassan Heydari

Bibliographic record

VenueSynthesis and Sintering · 2024
Typearticle
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThermodynamicsPerspective (graphical)High entropy alloysMaterials scienceStatistical physicsMetallurgyAlloyComputer sciencePhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

To save time and money before starting the production of a high entropy alloy (HEA), it is important to predict the possibility of HEA formation and the probable final microstructure using the solid solution phase formation thermodynamic rules. In this research, a step-by-step calculation of thermodynamic parameters is conducted to predict the possibility of formation and determine the final properties such as ∆Hmix­, ∆Smix, δr, δχ, Ω, VEC, and Tm for three Ni20Co20Cu15Fe20Mn25, Ni35Co20Cu5Fe5Mn35, and Ni5Co5Cu35Fe35Mn20 HEAs. Based on the obtained results, it is not possible to form a HEA with a solid solution structure for the Ni35Co20Cu5Fe5Mn35 and Ni5Co5Cu35Fe35Mn20 systems due to a low ∆Smix value of 11.28 J.mol-1.K-1. Based on the calculated values of ∆Hmix­, intermetallic compound formation and segregation are predicted for Ni35Co20Cu5Fe5Mn35 and Ni5Co5Cu35Fe35Mn20, respectively.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.270
Teacher spread0.259 · 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 designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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