Effects of Solute Segregation on Precipitation Phenomena and Age Hardening Response of High-Purity and Commercial AZ91 Magnesium Alloys
Bibliographic record
Abstract
In the present study, the continuous and discontinuous precipitation behavior of the commercial AZ91 alloy containing manganese and the AZ91 alloy produced from high-purity elemental components with no manganese addition has been investigated. It was found that for the commercial alloy, the solute manganese segregated within the primary α-Mg dendrites during solidification and played a major role in the initiation of non-uniform distribution of β-precipitates within the matrix grains. In addition, the solute manganese significantly suppressed the growth of discontinuous (lamellar) precipitates. The high-purity alloy also exhibited non-uniform precipitation. However, the precipitation patterns differed from those observed in the commercial alloy due to the inhomogeneous distribution of aluminum, the origin of which was rooted in the solute segregation within the interdendritic regions of the solidification structure. These differences in the precipitation mode caused by the presence or absence of manganese influenced the age hardening of the alloys. The high-purity specimens aged at lower temperatures attained higher peak-hardness owing to greater area fractions of discontinuous precipitation cells.
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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".