Effect of Al-Ti-B Based Master Alloys on Grain Refinement and Hot Tearing Susceptibility of AZ91E Magnesium Alloy
Bibliographic record
Abstract
The objective of this study was to examine the potential of Al-5Ti-1B and Al-1Ti-3B master alloys in reducing the hot tearing susceptibility of AZ91E magnesium alloy. The low penetration of magnesium alloys for structural automotive applications can be attributed to their poor castability during permanent mould casting. An improvement in the castability of magnesium alloys will result in the production of larger castings for automotive applications and a reduction in vehicle weight. The addition levels examined for both master alloys were 0.1, 0.2, 0.5 and 1.0 wt.%. The master alloys were added to the AZ91E alloy and stirred for 30 seconds. For the graphite mould castings used to observe grain refinement, the pouring and mould temperatures were 720 and 750 °C respectively. The hot tear castings were produced using a “dog bone” shaped H-13 tool steel mould. The pouring and mould temperatures were 720 and 180 °C respectively. Without master alloy addition, the base AZ91E casting had severe hot tears. The addition of Al-5Ti-1B slightly reduced hot tears while Al-1Ti-3B addition significantly reduced hot tears. The addition of Al-1Ti-3B also significantly reduced the grain size of the castings from 113 µm in the base alloy to 72 µm with 1.0 wt.% addition. The addition of Al-5Ti-1B did not lead to a reduction of hot tears because of large TiAl 3 particles acting as stress risers during solidification.
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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 | 0.002 | 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) | 0.000 | 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".