A Review on the Analysis of Thermal and Thermodynamic Aspects of Grain Refinement of Aluminum-Silicon-Based Alloys
Bibliographic record
Abstract
The present analysis addresses the solidification and thermodynamic parameters involved during the solidification of aluminum (Al)-based alloys as presented in the literature using different systems viz., binary aluminum-boron (Al-B) and aluminum-titanium (Al-Ti) systems, ternary aluminum-titanium-boron (Al-Ti-B) and aluminum-titanium-carbon (Al-Ti-C) systems, as well as taking into consideration the silicon-titanium-aluminide (Si-TiAl3) interaction in Al-based alloys containing Si. The analysis is supported by recent metallographic evidence obtained by the authors on A356.2 alloys. The sections on thermodynamic aspects cover the different models proposed concerning nucleation and growth on a newly formed Al grain. The value of the recalescence parameter reduces gradually with the increase in the Ti added. At a level of 0.20 wt%, this parameter becomes zero. If the concentration of grain refiner exceeds a certain amount, the grain size becomes minimal. Another parameter to be considered is the interaction between the grain refiner and traces of other metals in the base alloy. For example, Al-4%B can react with traces of Ti that may exist in the base alloy, leading to the reaction between boron and titanium to form titanium diboride (TiB2). Grain refinement is achieved primarily with TiB2 rather than aluminum diboride (AlB2), or both, depending on the Ti content in the given alloy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".