Corrosion resistance of squeeze cast magnesium alloy AM60-based hybrid nanocomposite coated with plasma electrolytic oxidation
Bibliographic record
Abstract
Plasma electrolytic oxidation (PEO) coating with NaAlO2 and KOH electrolytes was applied on the surfaces of as-cast AM60 (PEO-AM60), 7 vol.% Al2O3 fibres/AM60 (PEO-7FC) and 7 vol.% Al2O3 fibres + 3 vol.% Al2O3 nano-sized particles/AM60 (PEO-MHNC-7F3NP) to improve their corrosion resistance. The SEM and EDS analyses indicated that the PEO coating process formed a porous and dense layer on the substrate surface, as well as MgAl2O4 was the major concentration of the coating. The thickness of PEO coating on the 7FC and MHNC-7F3NP composites was slightly less than the coating on the AM60. The electrochemical corrosion tests were carried out in 3.5% NaCl aqueous solution at room temperature for investigating the corrosion behaviour of the as-cast AM60 and the composites after applying the PEO coating. The PEO coating increased the corrosion resistance of the AM60 alloy and the 7FC and MHNC-7F3NP composites to 342.81, 301.73 and 290.44 from 4.07, 2.08 and 1.88 kΩ∙cm2. By comparing the corrosion test results of the coated AM60 and the composites with those of the uncoated counterparts, it was found that the PEO coating significantly improved the corrosion resistance by up to 154 times. The addition of nano-sized particles barely increased the corrosion rate of the composite.
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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".