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Record W4402226288 · doi:10.3390/ma17174378

Theoretical Analysis of Stacking Fault Energy, Elastic Properties, Electronic Properties, and Work Function of MnxCoCrFeNi High-Entropy Alloy

2024· article· en· W4402226288 on OpenAlexaff
Fenger Sun, Guowei Zhang, Hong Xu, Dongyang Li, Yizheng Fu

Bibliographic record

VenueMaterials · 2024
Typearticle
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceStacking-fault energyHigh entropy alloysAlloySlip (aerodynamics)Density functional theoryCrystal twinningDislocationStacking faultWork (physics)Deformation (meteorology)Composite materialThermodynamicsMicrostructureComputational chemistryChemistry

Abstract

fetched live from OpenAlex

The effects of different Mn concentrations on the generalized stacking fault energies (GSFE) and elastic properties of MnxCoCrFeNi high-entropy alloys (HEAs) have been studied via first-principles, which are based on density functional theory. The relationship of different Mn concentrations with the chemical bond and surface activity of MnxCoCrFeNi HEAs are discussed from the perspectives of electronic structure and work function. The results show that the plastic deformation of MnxCoCrFeNi HEAs can be controlled via dislocation-mediated slip. But with the increase in Mn concentration, mechanical micro twinning can still be formed. The deformation resistance, shear resistance, and stiffness of MnxCoCrFeNi HEAs increase with the enhancement of Mn content. Accordingly, in the case of increased Mn concentration, the weakening of atomic bonds in MnxCoCrFeNi HEAs leads to the increase in alloy instability, which improves the possibility of dislocation.

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 score0.113
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.183
Teacher spread0.174 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

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