Comparative Abrasive Wear Study of HVOF Coatings Obtained by Spraying WC-17Co Microcrystalline and Duplex Near-Nanocrystalline Cermet Powders
Bibliographic record
Abstract
High velocity oxy-fuel spraying was used to develop a near-nanocrystalline coating from a duplex Co coated WC-17Co powder feedstock. A microstructural and mechanical property characterization of the coating with a similar microcrystalline coating of the same composition was made. X-ray diffraction analysis showed less decarburization of the nanocrystalline coating and a more homogeneous coating structure than the microcrystalline coating produced under the same spraying conditions. The mechanical assessment of the coatings was performed using microhardness and indentation fracture toughness measurements. The abrasive wear resistance was determined using the ASTM G65-04 dry-sand rubber wheel test. The results showed that the hardness of the near-nanocrystalline coating was 25% greater than that of the microcrystalline coating and a sixfold increase in the abrasive wear resistance was also recorded for the near-nanocrystalline coating. Examination of the worn surfaces using atomic force microscopy after abrasive testing showed a smoother surface roughness in the near-nanocrystalline coating than that of the microcrystalline coating surface. The increase in fracture toughness of the near-nanocrystalline coating prevented brittle fracture of the coating surface.
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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".