Study of Dynamic Precipitation during Hot Deformation of Mg-Al-Sn Alloys
Bibliographic record
Abstract
The objective of this work is to investigate the effect of dynamic precipitation on the hot deformation behaviour of magnesium. Mg-Al-Sn alloys have been designed using thermodynamic modeling software, FactSage, based on precipitation of Mg2Sn at hot deformation temperatures. Uniaxial compression has been introduced at the temperature range of 250-350 °C to enhance the formation of precipitates. The flow behaviour and microstructural evolvement were studied for a strain rate of 0.01 /sand deformation degree of 90 %. Dynamic recrystallization (DRX) occurs in this study and it is found that the volume percent of dynamic recrystallization and dynamically recrystallized grain size are related to the amount of precipitation formed during deformation. The formation of Mg2Sn precipitates during the dynamic recrystallization process may retard the dynamic recrystallization and slow down the grain growth by precipitation pinning effect at the DRX grain boundaries, resulting in a finer grain size.
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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".