On thermal analysis, macrostructure and microstructure of grain refined Al–Si–Mg cast alloys: role of Sr addition
Bibliographic record
Abstract
The present study aimed at investigating the influence of grain refinement in combination with Sr modification on the solidification behaviour of A356·2 alloy, and the resulting micro- and macrostructures obtained. Grain refinement of A356·2 alloy using Ti and B additions in the ranges of 0·02–0·5% and 0·01–0·5% respectively was studied using five different grain refiners in the form of Al–10%Ti, Al–5%Ti–1%B, Al–2·5%Ti–2·5%B, Al–1·7%Ti–1·4%%B and Al–4%B aluminium master alloys. Sr modification of the alloys was carried out using Sr additions of 30 and 200 ppm in the form of Al–10%Sr master alloy. The probable interactions between Sr and Ti and Sr and B were investigated using different metallographic techniques. Thermal analysis was also used to evaluate these interactions. Electron microprobe analysis revealed that adding >0·1%B to the A356·2 alloy may lead to formation of particles predominantly containing B and Sr, with a composition approaching SrB6.
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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".