Effect of Cooling Rates on the Microstructure Evolution and Eutectic Formation of As-cast Mg-Al-Ca Alloys
Bibliographic record
Abstract
A Mg-5.0wt.%Al-2.0wt.%Ca alloy (AC52) was cast at different cooling rates varying from 0.5 to 65 °C/s. The dendrites was characterized by determining the secondary dendrite arm spacing (SDAS) and the volume fraction of secondary eutectic phases with the linear intercept and point counting methods, respectively. The SDAS decreases significantly with increasing cooling rates, while the volume fraction of the eutectic phase increases from 10.8 ± 1.44 vol.% at 0.5 °C/s to 20.4 ± 1.52 vol.% at 20 °C/s. However, a further increase in cooling rate beyond 20 °C/s has limited influence on the volume fraction of eutectic phases. A large number of dispersed eutectic phases were observed in the primary α-Mg of the alloys cast at low cooling rates. Although, at the microscale, there were no dispersed eutectic phases in alloys cast at a high cooling rate of 30 °C/s, nanoscale eutectic phases were found by TEM observation. The dimensions and morphology of the Al8Mn5 phase were also dependent on the cooling rates. When cooling rates were high, the size of Al8Mn5 particles was relatively small compared to that observed at low cooling rates. The majority of Al8Mn5 particles were found to be attached to the eutectic phases, which implies the possible nucleation of the eutectic phase on the Al8Mn5 particles present in the melt.
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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".