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Record W4403714668 · doi:10.1088/1361-651x/ad8ada

Strengthening by {110} and {112} edge dislocations in BCC high entropy alloys

2024· article· en· W4403714668 on OpenAlexaff
Xin Liu, Rui Barreira, Masoud Rahbar Niazi, W.A. Curtin

Bibliographic record

VenueModelling and Simulation in Materials Science and Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersNational Center of Competence in Research Materials’ Revolution: Computational Design and Discovery of Novel Materials
KeywordsMaterials scienceHigh entropy alloysCondensed matter physicsEnhanced Data Rates for GSM EvolutionCrystallographyAlloyMetallurgyPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Mechanical tests and microscopy studies on body-centered cubic (BCC) high entropy alloys reveal transitions from screw to edge dislocation slip and from {110} to {112} slip plane activity. Here, a strengthening theory for BCC edge dislocation slip on {112} planes is thus developed that parallels a recent theory for {110} slip. Using the atomistic dislocation pressure fields for four BCC elements (Nb, Ta, Mo, W) as proxies to span the range of likely alloy cores, theory predicts that the zero temperature yield strength for {112} slip is slightly lower (0%–20%) than that for {110} slip but that the associated energy barrier is slightly (0%–20%) higher. This leads to cancelling effects, and hence very similar strengths, at finite temperatures and strain rates. Full atomistic results on selected dilute binary alloys show some shifts in these trends, but with similar magnitudes and cancelling effects. The close strengths of {110} and {112} slip modes indicate that subtle aspects beyond the scope of the theory will determine which slip system controls the observed strengthening. This closeness in strength cements the use of the {110} edge theory for guiding alloy design independent of actual slip system.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.218
Teacher spread0.209 · 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 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

Citations7
Published2024
Admission routes1
Has abstractyes

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