Corrosion and microstructure of as-cast magnesium alloy AM60-based hybrid nanocomposite
Bibliographic record
Abstract
Two types of Mg alloy AM60-based composites containing (1) only 7 vol.% Al2O3 Fibre and (2) both 7 vol.% Al2O3 Fibre + 3 vol.% Al2O3 nano-Particle, named 7FC and MHNC-7F3NP, respectively, as well as the unreinforced matrix alloy AM60 were prepared by using the preform-squeeze casting technique. The microstructure of the matrix alloy AM60 characterised by optical microscopy (OM), scanning electron microscopy (SEM) and X-ray energy dispersive spectroscopy (EDS) consisted of primary α-Mg grains, eutectic β-Mg17Al12 phases and Al-Mn intermetallics, of which distribution were different from those in the composites. The reinforcement introduction refined the matrix grain structure of the composites significantly. The corrosion behaviours of the 7FC and MHNC-7F3NP composites and the matrix alloy were investigated by using the potential-dynamic polarisation test in 3.5 wt.% NaCl aqueous solution. Compared with the matrix alloy, the introduction of micron-sized alumina fibres decreased the corrosion resistance of the matrix alloy AM60 considerably due to the presence of excessive interfaces, while the high density of grain boundaries and the absence of noble precipitates such as β-Mg17Al12 phases and Al-Mn intermetallics at the grain boundaries in the composites should also be somewhat responsible for their poor corrosion resistance. The addition of the nano-sized particles led to almost no further reduction in the corrosion resistance of the MHNC-7F3NP.
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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 | 0.000 | 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) | 0.000 | 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".