Structure, Mechanical and Tribological Properties of HVOF Sprayed (WC-Co+Al) Composite Coating on Ductile Cast Iron
Bibliographic record
Abstract
The paper presents the results of examinations of WC-Co coating sprayed on ductile cast iron by high velocity oxygen fuel spray process (HVOF) with powder containing Al particles in an amount of 10%. The impact of Al particles added to the tungsten carbide coating on the structure, mechanical and tribological properties in the system of (WC-C)/ductile cast iron was examined. The microstructure of the thermal sprayed WC-Co+Al coating was characterized by light, scanning electron (SEM) and transmission electron (TEM) microscopes as well as the analysis of chemical and phase composition in micro areas (EDS, XRD). It was found that by supersonic thermal spraying with WC-Co powders with the addition of Al particles, the coatings of low porosity, high hardness, a very good adhesion to the substrate, compact structure with molten Al particles and finely fragmented WC particles embedded in a cobalt matrix, reaching the nanocrystalline sizes were obtained. Moreover, the results were discussed in reference to examination of bending strength considering cracking and delamination in the system of (WC-Co+Al)/ductile cast iron as well as hardness and wear resistance of the coating. It was found that the addition of Al particles was significantly increase resistance to cracking and wear behaviour in the studied system
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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".