Improved Wear Performance by the Incorporation of Solid Lubricants During Thermal Spraying
Bibliographic record
Abstract
Abstract For components that are required to function in sliding or rubbing contact with other parts, degradation often occurs through wear due to friction between the two contacting surfaces. Depending on the nature of the materials being used, the addition of water as a lubricant may introduce corrosion and accelerate the degradation process. To improve the performance and increase the life of these components, coatings may be applied to the regions subject to the greatest wear. These coatings may be engineered to provide internal pockets of solid lubricant in order to improve the tribological performance. In the present study, coatings containing a solid lubricant were produced by thermal spraying feedstock powders consisting of a blend of tungsten carbide-metal and a fluorinated ethylene-propylene copolymer-based material. The volume content of this Teflon-based material in the feedstock ranged from 3.5 to 36%. These feedstocks were deposited using a high velocity oxy-fuel system to produce coatings having a level of porosity below 2%. Sliding wear tests in which coated rotors were tested in contact with stationary carbon-graphite disks identified an optimum level of Teflon-based material in the feedstock formulation required to produce coatings exhibiting minimum wear. This optimum level was in the range of 7-17% by volume and depended on the composition of the cermet constituent. Reductions in mass loss for the couples on the order of 50% (an improvement in performance by a factor of approximately two) were obtained for the best-performing compositions, as compared to couples m which the coating contained no solid lubricant.
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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 | 0.000 |
| 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 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".