Effect of grain refinement on the microstructure, dendrite coherency and porosity of AZ91E magnesium alloy
Bibliographic record
Abstract
Magnesium (Mg) alloys present a promising alternative to aluminum (Al) alloys in lightweight applications. However, relative to Al alloys, Mg alloys have poor castability. Castability is influenced significantly by the dendrite coherency point (DCP), which represents the temperature, time, and solid fraction at which an interlocking solid network forms during solidification. An increase in the solid fraction at coherency may improve the castability of the alloy and reduce casting defects such as porosity, hot tears and misruns. A successful method for increasing the solid fraction at the DCP in Al alloys involves the use of grain refiners such as titanium (Ti). However, the influence of Ti refiners on the DCP in Mg alloys has not been thoroughly investigated. The objective of this research was to study the effect of Al-5Ti-1B refiner on the dendrite growth mechanism, DCP and porosity of AZ91E magnesium alloy. This thesis is a pioneering effort in relating the grain refinement effect of Ti on the DCP, coherency solid fraction, and porosity development during the solidification of Mg alloy, AZ91E. It represents an important step in improving the castability of Mg alloys. Varying levels of Al-5Ti1B grain refiner (0.005, 0.05, 0.1, 0.2, and 0.3 wt.% Ti) were added to AZ91E. The effect of Al-5Ti-1B grain refiner on the microstructure and dendrite growth mechanism of AZ91E was investigated. Quench experiments were performed to observe transformations in the dendritic morphology that resulted from the refiner additions. The growth rate and DCP were determined using the rheological method. The changes in porosity levels were determined for the grain refiner additions.
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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".