Metallurgical Parameters Controlling the Eutectic Silicon Charateristics in Be-Treated Al-Si-Mg Alloys
Bibliographic record
Abstract
The present work was carried out on Al-7%Si-0.4%Mg-X alloy (where X = Mg, Fe, Sr or Be), where the effect of solidification rate on the eutectic silicon characteristics was investigated. Two solidification rates corresponding to dendrite arm spacings (DAS) of 24 and 65 μm were employed. Samples with 24 μm DAS were solution heat-treated at 540 °C for 5 and 12 h prior to quenching in warm water at 65 °C. Eutectic Si particle charateristics were measured using an image analyzer. The results show that the addition of 0.05% Be leads to partial modification of the Si particles. Full modification was only obtained when Sr was added in an amount of 150-200 ppm, depending on the applied solidification rate. Increasing the amount of Mg to 0.8% in Sr-modified alloys leads to a reduction in the effectiveness of Sr as the main modifier. Similar observations were made when the Fe content was increased in Be-treated alloys due to the Be-Fe interaction. Over-modification results in the precipitation of hard Sr-rich particles, mainly Al₄SrSi₂, whereas overheating causes incipient melting of the Al-Cu eutectic and hence the surrounding matrix. Both factors lead to a deterioration in the alloy mechanical properties. Furthermore, the presence of long, acicular Si particles accelerates the occurrence of fracture and, as a result, yields poor ductility. In low iron (less than 0.1 wt%) Al-Si-Mg alloys, the mechanical properties in the as cast, as well as heat treated conditions, are mainly controlled by the eutectic Si charatersitics. Increasing the iron content and, hence, the volume fraction of Fe-based intermetallics leads to a complex fracture mode.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".