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Record W4290852316 · doi:10.1126/sciadv.abp9096

Dynamic response of high-entropy alloys to ballistic impact

2022· article· en· W4290852316 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Advances · 2022
Typearticle
Languageen
FieldEngineering
TopicHigh Entropy Alloys Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBallistic impactHigh entropy alloysStatistical physicsMaterials sciencePhysicsAlloyMetallurgy

Abstract

fetched live from OpenAlex

High-entropy alloys (HEAs) are promising to provide effective antiballistic capability because of their superior mechanical properties. However, the twinning-active Cantor alloy is found less ballistic resistant, compared with its Mn-free companion. It is unclear how the HEAs resist ballistic impact and why Mn does not benefit the ballistic resistance. Here, we used molecular dynamics simulations to investigate the ballistic resistances of CrMnFeCoNi and CrFeCoNi and elucidate underlying mechanisms. It is shown that the alloys' ballistic resistances dominantly benefit from active dislocations generated at higher strain rates. Stronger atomic bonding and higher dislocation densities make the CrFeCoNi easier to be strain hardened with elevated toughness to resist high-speed deformation, while weaker atomic bonding and easier occurrence of dislocation tangling make CrMnFeCoNi less resistant to failure under ballistic impact. This work helps better understand the antiballistic behavior of HEAs and guide the design of armor and energy-absorption materials.

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.

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 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 score0.583
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.268
Teacher spread0.262 · 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