Strain Hardening of Heat Treated Nanostructured WC-17Co Coatings and Their Sliding Wear Behavior
Bibliographic record
Abstract
Grain size, their distribution and geometry are important to study the dislocation behavior and grain boundary sliding of ceramic reinforced metallic composite materials. Grain size reduction has been shown to lead to significant improvements of the wear resistance in nanostructured materials. As the grain size decreases from polycrystalline to nanocrystalline range, abrasive wear resistance increases considerably from the increased hardness and volume loss following Archard’s law of wear. Further, the heat treatment effect on the content of the metallic binder in a ceramic-metallic (cermet) material is thought to increase the hardness with decreasing crystalline size, thereby improving the sliding wear behavior of materials. In this study, the high velocity oxy-fuel (HVOF) thermal spraying of nanostructured WC-17Co coatings with engineered ‘duplex outer coating’ is conducted. The microhardness and sliding wear studies of the coatings and their heat-treated counterparts are performed. The nanostructured coatings showed a significant increase in the microhardness and wear resistance when compared with those of the conventional microstructured coatings of the same composition. It is believed that the improved performance is related with the work hardening as well as dispersion hardening of the nanostructured grains in the deposited coatings.
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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) | 0.000 | 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".