Dynamic response of high-entropy alloys to ballistic impact
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".