Thermodynamic Modeling and Experimental Measurement of Precipitation Formation during Dynamic Recrystallization for Magnesium Alloys
Bibliographic record
Abstract
Magnesium alloys have low formability at room temperature associated with its hexagonal closed pack structure. Formation of precipitates during deformation may pin the grain boundary and reduce the final grain size, which literally means the improvement of formability. The aim of this study is to design magnesium alloys that are capable of forming precipitate during hot deformation. Thermodynamic modeling software, FactSage, has been used to design Mg-Al-Sn alloys based on forming target Mg2Sn precipitate at hot deformation temperatures between 250 and 350oC. Uniaxial compression at elevated temperatures has been performed to simulate the hot deformation behaviour as well as to enhance the formation of precipitates. Strain rates used in this study were in the range of 1.0 to 0.001s-1 for a constant deformation degree of 90%. It was found that the formation of precipitate depends on deformation temperature and strain rate. Measured amounts of precipitate were compared with the calculated equilibrium results from FactSage.
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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 | 0.001 |
| 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 | 0.001 | 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".