Comparative Сharacteristics of the Structureand Functional Properties of Coatings Formed on Aluminum Alloys 2ххх and 7ххх Series by the Method of Plasma Electrolytic Oxidation
Bibliographic record
Abstract
The structure and properties of coatings formed on 2ххх and 7ххх aluminum alloys by plasma elec-trolytic oxidation (PEO) performed under the same conditions have been studied. The substrate material is shown to substantially affect the quality, structure, and properties of formed coatings. Compared to the D16 Т (4Cu, 1.4Mg wt %) alloy substrate, the V95 Т1 (6.2Zn, 2.4Mg, 1.7Cu wt %) alloy substrate favors the for-mation of coatings with a more homogeneous composition and uniform thickness, which exhibit great cohe-sive and adhesive strength and mechanical and tribological properties. The adhesive failure of PEO coatings formed on the V95 Т1 alloy occurs at a load of 63 N, which is substantially higher than the critical load (49 N) of coatings formed on the D16 T alloy. The maximum hardness of coatings formed on the V95 Т1 alloy is 25 GPa, which exceeds that of coatings formed on the D16 T alloy and is equal to 20 GPa. The wear resistance of coating in water, which is formed on the V95 Т1 alloy is 4.4 times higher compared to that of the wear-resistant coating formed on the D16 T alloy.
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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 | 0.001 | 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".