Effect of manganese and silicon on iron intermetallics in 206 foundry alloy
Bibliographic record
Abstract
Iron is one of common impurities in 206 alloys and detrimental platelet-like iron intermetallics can easily form at high iron contents resulted from the increasing use of recycled aluminum alloys. The present work has investigated the iron intermetallics formed in Al-4.5 wt.% Cu alloy with 0.3 wt.% Fe and the effect of Mn and Si on the morphology and transformation of these iron intermetallics using thermal analysis, image analysis, differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). The results show that there are three major types of iron intermetallics according to their morphologies: platelet-like, block and Chinese script. It is observed that single addition of either Mn or Si, even at high contents, can only partially convert the iron intermetallics from platelet-like to Chinese script. All the platelet-like iron intermetallics can be transformed to Chinese script at appropriate addition of both Mn and Si with a combination of 0.3 wt% Mn and 0.3 wt% Si.
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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".