Influence of Minor Additions of Be on the Eutectic Modification of an Al-33wt.%Cu Alloy Solidified under Transient Conditions
Bibliographic record
Abstract
Al-based alloys are often selected for use in various engineering applications as well as in the aircraft and aerospace industry. The improvement of their performances under severe conditions have required the use of alloying elements. In the present work, Be is added to the eutectic Al-33 wt.%Cu alloy with a view to investigating the resulting effects on microstructural features and hardness. A directional solidification technique is used, yielding a wide range of solidification cooling rates. This permits microstructural features to be investigated with emphasis on the role of Be on the eutectic morphology. The directionally solidified microstructures are formed by eutectic colonies for the Al-33 wt.%Cu alloy, however, with additions of both 0.05 and 0.5 wt.% Be, the original cell-like morphology is transformed into a trefoil-like morphology. This together with the α-Al dendritic pattern characterize the microstructure of the Al-33Cu-Be alloys examined. Solidification growth laws are experimentally derived relating dendritic and eutectic colony spacings to solidification cooling rates and growth rates. The length scale of such spacings is shown not to affect the Vickers hardness of the Al-33Cu-Be alloys examined; however, the additions of Be are shown to improve the brittle behavior of the Al-33 wt.%Cu alloy.
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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".