Phase precipitation in transition metal-containing 354-type alloys
Bibliographic record
Abstract
Abstract The present study was carried out to investigate the effects of Ni, Mn, Zr, and Sc additions, individually or in combination, on the microstructure of 354 casting alloy (Al-9 wt.% Si-1.8 wt.% Cu-0.5 wt.% Mg). Microstructural examination and thermal analysis data showed that the main reactions detected during the solidification of the six 354 alloys (G1, G6–G10) investigated are: formation of the α-Al dendritic network; precipitation of Al-Si eutectic and post-eutectic β-Al5FeSi; Mg2Si phase; transformation of the β-phase into π-Al8Mg3FeSi6 phase; and precipitation of Al2Cu and Q-Al5Mg8Cu2Si6 phases. With 2 wt.% Ni addition, the formation of Al9FeNi and Al3CuNi phases is observed. In the base 354 alloy the main phases are restricted to Cu-, Mg-, and Fe-rich intermetallic phases. The Si particle characteristics and volume fraction of intermetallics are influenced by the solidification rate and Mg level, whereas addition of Fe and/or Mn has no significant influence. In alloy G9, Fe, Mn and Ni interact to form new intermetallic phases. An increased Fe content leads to formation of polyhedral/star-like sludge particles in addition to α-Fe and β-Al5FeSi phases; the presence of the hard sludge particles within the soft α-Al dendrites improves the alloy properties.
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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".