Effect of graphene on the microstructure, mechanical properties, and wear behavior of plasma‐sprayed Al <sub>2</sub> O <sub>3</sub> –Cr <sub>2</sub> O <sub>3</sub> coating
Bibliographic record
Abstract
Abstract In this study, plasma‐sprayed Al 2 O 3 –Cr 2 O 3 coatings with different contents of graphene nanosheets were prepared for investigating effects of the graphene on microstructure, mechanical properties, and wear behavior of the coating. The experimental results showed that graphene increased the porosity and the microhardness of the coating. But excessive graphene decreased the microhardness remarkably. Besides, the anti‐crack initiation and propagation abilities of the coatings with graphene improved significantly. The wear rate of the coatings decreased first, and then increased with increasing the graphene content. Impressively, the wear rates of the coating with 2.9% graphene decreased by 33.5% and 36.7%, compared with those of the coating without graphene under normal loads of 5 and 15 N, respectively. The main wear mechanisms of the coatings with and without graphene are brittle fracture and abrasive wear.
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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".