Effects of La and Ce Addition on the Modification of Al-Si Based Alloys
Bibliographic record
Abstract
This study focuses on the effects of the addition of rare earth metals (mainly lanthanum and cerium) on the eutectic Si characteristics in Al-Si based alloys. Based on the solidification curves and microstructural examination of the corresponding alloys, it was found that addition of La or Ce increases the alloy melting temperature and the Al-Si eutectic temperature, with an Al-Si recalescence of 2-3°C, and the appearance of post-α-Al peaks attributed to precipitation of rare earth intermetallics. Addition of La or Ce to Al-(7–13)% Si causes only partial modification of the eutectic Si particles. Lanthanum has a high affinity to react with Sr, which weakens the modification efficiency of the latter. Cerium, however, has a high affinity for Ti, forming a large amount of sludge. Due to the large difference in the length of the eutectic Si particles in the same sample, the normal use of standard deviation in this case is meaningless.
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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) | 0.000 | 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".