Tuning the creep rates of binary Al alloys by considering the effects of the stacking faults, alloying elements, and elastic moduli: a first-principles study
Bibliographic record
Abstract
Using first-principles calculations, the effects of intrinsic stacking faults, elastic moduli, and diffusivity on the creep rates of aluminum alloys Al–X (X = Sc, Nb, or Mo) have been investigated. The calculated stacking fault energies of dilute Al show stabilization in the case of Sc and destabilization in the case of Mo and Nb. Although all three impurities confer stiffer elastic properties, Sc appears to retain the ductility of Al but Mo and Nb push the system in the brittle regime. Also, Mo and Nb strongly increase the activation barrier to diffusion, leading to much reduced creep. The results indicate that Mo and Nb can be used in Al alloys to improve elastic properties and creep resistance but only at very low levels, before brittleness becomes an issue.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".