Effect of heat treatment on the microstructure and corrosion behaviour of Mg–Zn alloys
Bibliographic record
Abstract
Microstructure and corrosion behaviour in simulated body fluid of as‐cast and heat treated Mg–xZn (x = 3 and 6) alloys for different heat treatment times were studied. The results revealed that as‐cast Mg–3Zn alloys consist of Mg12Zn13 phase and α‐Mg matrix, while Mg–6Zn is composed of Mg51Zn20, Mg12Zn13 compounds and α‐Mg matrix. After heat treatment of Mg–6Zn alloy at 340 °C, the Mg51Zn20 phase decomposed to the matrix and Mg12Zn13 while, the microstructure of Mg–3Zn remained unchanged. The results also indicated that heat treatment at 340 °C has little influence on the corrosion behaviour of Mg–3Zn. In contrast, heat treatment improved the corrosion resistance of the Mg–6Zn alloy as the decomposition of the Mg51Zn20 phase decreased micro‐galvanic corrosion. The corrosion resistance of both as‐cast Mg–3Zn and Mg–6Zn alloys marginally improved with increasing heat treatment times.
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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".