Dynamic characterization of Cu–Zr binary bulk metallic glasses: A molecular dynamics study
Bibliographic record
Abstract
In the present study, a molecular dynamics simulation employing embedded atom method potential is performed to investigate the formation and characterization of CuZr bulk metallic glasses (BMGs). To elucidate the effect of component concentration of three samples of BMGs including Cu25Zr75, Cu50Zr50, and Cu75Zr25 that are formed by melt quenching. The local structure of BMGs is analyzed by means of radial distribution function and local atomic number density, ρ. The mechanical behavior of three compositions is investigated using uniaxial compressive loading at a constant strain rate. It is revealed from the results that yield strength increases with increasing Cu concentration. Thermal expansion of CuZr BMGs is examined and variation in length and volume is measured. The analysis revealed that Cu25Zr75, and Cu50Zr50 exhibited the typical expansion behavior while Cu75Zr25 showed an anomalous behavior.
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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) | 0.001 | 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".