Cold-Sprayed WC-Ni-Cu MMC Coatings with Improved Hardness
Bibliographic record
Abstract
Abstract Cold-gas dynamic spraying (“cold-spraying”) at low pressure (1034kPa/150 psig) was used to fabricate WC-Ni-Cu metal matrix composite (MMC) coatings. Tungsten carbide (WC)- based powder was mechanically blended with nickel (Ni) and copper (Cu) powder at various compositions. X-ray diffraction (XRD), scanning electron microscopy (SEM), and Vickers micro-hardness testing were conducted on the cold-sprayed coatings. Image analysis was used to determine the WC content in the coatings. XRD profiles showed that no decarburization or oxidation of the WC reinforcing particles occurred in any of the coatings. The WC content in the coatings increased as the WC content in the powder increased, but did not increase further beyond 96 wt. % WC content in the powder blend. The results from Vickers micro-hardness testing confirmed that the coatings with the highest amount of WC had the highest hardness value. The coatings fabricated with a powder composition of 96 wt. % WC + 2 wt. % Ni + 2 wt. % Cu yielded a hardness of 385 ± 73 HV0.3/10 (n = 50). These results suggest that it is possible to use cold-spraying at low pressure to fabricate WC-based MMC coatings with improved hardness.
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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) | 0.001 | 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 | 0.001 | 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".