Effects of Zr and Sc additions on precipitation of α-Al(FeMn)Si dispersoids under various heat treatments in Al–Mg–Si AA6082 alloys
Bibliographic record
Abstract
Abstract The present work investigated the influence of Zr and Sc on the evolution of α-Al(FeMn)Si dispersoids (“α-dispersoids") in Al–Mg–Si alloys. Both the individual addition of Zr and the combined additions of Sc and Zr increased the size but decreased the number density of the α-dispersoids, indicating the reduction in the formation of α-dispersoids. However, the reduction levels were the most significant when heat-treated at 350 °C in the alloy with both Sc and Zr and at 400 ° C in the alloy with only Zr, which were likely related to the different interactions between intermediate B’ precipitates and α-dispersoids with the addition of Zr and Sc. Although the α-dispersoids were suppressed in the Zr/Sc-containing alloys, their microhardness was generally higher than the base alloy, which can be attributed to the strengthening contribution induced by Zr and Sc either from their solid solution hardening or the precipitation hardening of Al 3 Zr/Al 3 (Sc, Zr) dispersoids.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".