Glaze layer on Co-Cr3C2 composite coatings sprayed by HVOF
Bibliographic record
Abstract
Stellite 6, a cobalt-based alloy, exhibits excellent resistance against oxidation, corrosion, and wear. At elevated temperatures, they form a protective glaze layer during sliding, transforming wear behavior from severe to mild. While Stellite 6 coatings have been extensively explored, post-processing is commonly employed to enhance carbide segregation, a characteristic of these alloys. In this investigation, chromium-carbide was added during the spraying process to explore the effects of static oxidation (without wear) and the glaze layer formation during wear at elevated temperatures in Stellite 6 composite coatings produced by HVOF. This study compares the wear and oxidation mechanisms, considering varying volume percentages of carbides using advanced characterization techniques, such as scanning electron microscopy (SEM), high-resolution scanning transmission electron microscopy (STEM), and Raman spectroscopy. The addition of carbides facilitates the glaze layer formation on the coating at 300 °C, and a higher carbide content reduces the number of cycles needed for its formation. This is attributed to the homogeneous distribution of the hard phase within the coating, combined with the distinct oxidation mechanisms of HVOF spraying (e.g., chromium retention in the matrix, pore formation, and splat boundaries). • Cr 3 C 2 added to Stellite 6 HVOF coating accelerates the glaze layer formation. • Glaze layer is composed of a multilayer of oxides. • Top layer surface in contact is a hard 200 nm thick mix of Co Cr oxide. • Oxidation resistance of the HVOF coatings is better than bulk Stellite 6.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".