A molecular dynamics study of twin width, grain size and temperature effects on the toughness of 2D-columnar nanotwinned copper
Bibliographic record
Abstract
The introduction of twin boundaries (TBs) within nanocrystalline grains has given scientists an opportunity to enhance mechanical properties that are usually mutually exclusive: strength and ductility. This research is focused on developing a complete understanding of the influences of twin width, grain size and temperature on the deformation characteristics and properties of nanotwinned Cu by large-scale molecular dynamics simulations. Simulation results have shown that a material's toughness can be enhanced by introducing nanotwins, and the enhancement is more pronounced for the higher twin density structures and at lower temperatures. Nanotwinned grains are found to be highly anisotropic in their plastic response; ductile along TBs but strong across them. A random polycrystalline sample gains toughness through the combined response of variously oriented grains. At extremely low temperature, toughness values are elevated further due to depressed dislocation activities inside the grains. The study has also revealed that, unlike twin width refinement, grain size refinement may not always yield superior properties, and may deteriorate material toughness.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".