Feedstock powder considerations for miniaturized inner-diameter HOVF systems for the deposition of WC-Co-Cr coatings
Bibliographic record
Abstract
Emerging miniature HVOF systems offer new opportunities to replace hard-chrome plating with sprayed carbide coatings in space restricted inner-diameters in aerospace and industrial application. The worldwide interest in this technology is largely driven by regularity restrictions for the continuation of downstream use of hexavalent chrome, such as REACH. While feedstock supply chains for conventional HVOF WC-Co-Cr are well established since decades, the lower flame enthalpies and shorter spray distances used for the scaled-down HVOF systems impose smaller particle size cuts as customized to the particular spray system to attain sufficient particle heating and acceleration. This presentation discusses the feedstock particle size and size distribution considerations for the liquid fueled Praxair TAFA Model 825 JPid, the hydrogen fueled Spraywerx ID-NOVA MK-6 HVOF, and the Uniquecoat i7 HVAF systems for the deposition of wear protective WC-Co-Cr coatings. A variety of custom manufactured and commercially available powders are compared and suitable windows for particle size distributions, torch input powers and spray distances are delineated for the deposition of coatings exceeding harness values of 950 HV300gf, porosities below 1%, and ASTM 65 abrasion wear loss below 0.1g per 6000 revolutions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".