Corrosion and corrosion fatigue performances of micro‐arc oxidation coating on AZ31B cast magnesium alloy
Bibliographic record
Abstract
In this work, the corrosion performances of micro‐arc oxidation (MAO) coating on AZ31B cast alloy were examined. MAO coating synthesized at a low current density of 34 mA/cm 2 has a uniform and compact microstructure with very fine micro‐pores and few structural defects; thus, robust protection is provided for the AZ31B substrate in corrosive solutions. The long‐term corrosion and corrosion fatigue behaviors of the MAO coatings formed at the optimal current density for 5 and 10 min were characterized. The results show that the MAO coating formed for 10 min provides greater protection in a salt fog environment than the coating formed for 5 min does because it is thicker. The fatigue life and fracture analysis of bare, MAO‐coated and E‐paint MAO‐coated AZ31B indicate that the MAO coating reduces corrosion fatigue life by 55% due to the micro‐pores and micro‐cracks on its surface providing initiation sites under stress conditions and accelerating crack propagation. However, E‐paint MAO‐coated specimens show improved corrosion fatigue strength in 10 7 cycles at ∼60 and ∼50 MPa under the same conditions due to the sealing of the micro‐pores and micro‐cracks in the MAO coatings.
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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".