Low Friction and High Wear Resistance of Plasma Electrolytic Oxidation (PEO)-Coated AZ31 Mg Alloy Sliding against Hydrogenated DLC (a-C-H) at Elevated Temperatures
Bibliographic record
Abstract
Plasma electrolytic oxidation (PEO) treatment of Mg alloys improves their wear resistance by increasing their surface hardness, but also leads to high coefficient of friction (COF) values. The sliding counterfaces and the conditions under which PEO-coated Mg alloys operate affect their COFs. PEO-coated AZ31 alloy sliding against hydrogenated DLC (a-C-H) coated steel yields a low COF of 0.13 under the ambient conditions. The current study investigates the effect of the test temperature on the tribological behavior of PEO-coated AZ31 Mg samples sliding against the a-C-H coated counterface at temperatures up to 300 °C. According to the COF vs. wear rate diagram constructed in the temperature range of 25–250 °C, lower COF values and wear rates were exhibited by PEO-coated AZ31 sliding against a-C-H compared to uncoated AZ31 sliding against a-C-H, and PEO coated AZ31 sliding against an uncoated ASTM 52100 steel. The PEO-coated AZ31 produced the lowest COF of 0.03 at 200 °C. The application of PEO to the Mg alloy automotive cylinder bores running against DLC-coated piston rings and/or PEO-coated Mg alloy pistons running against DLC-coated bores could provide a new approach for the prevention of seizure and hot scuffing in lightweight engines in the temperature range between 150–250 °C.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".