High-Temperature Wear Performance of Laser-Cladded NiCrBSi/60 wt% WC Composite Coating on SS316L Alloy
Bibliographic record
Abstract
Abstract This investigation reports on the processing and characterization of NiCrBSi/60 wt% WC composite claddings on SS316L steel substrates by laser cladding process. Microstructural analyses conducted using a scanning electron microscope, an energy dispersive spectrometer, and X-ray diffraction confirmed the successful development of dense cladding layers containing WC reinforcement phases. Microhardness testing revealed a substantial increase in hardness within the clad layer, reaching approximately 1086 HV0.2, significantly higher than the 190 HV0.2 of the SS316L. As the testing temperature increases, the wear-rate and the coefficient of friction (COF) of the coated sample decrease, making it applicable in high-temperature applications. The observed reduction in the COF at higher testing temperatures is attributed to the formation of a lubricious oxide layer that serves as a protective barrier, preventing direct contact between the coated sample and the hard counter disc. Tribological experiments conducted at room temperature, 350 °C, and 700 °C demonstrated a progressive increase in wear-rate with temperature, especially beyond 350 °C, attributed to thermal softening, oxide layer formation, and wear transformations. At 700 °C, oxidation and delamination were the prominent mechanisms. Compared to room temperature, wear resistance decreased by 559.5% at 700 °C, with reductions of 381.1% observed at 350 °C. These findings underscore the critical role of WC reinforcements in retaining wear resistance up to 350 °C. Conversely, at 700 °C, intensified oxidation and matrix softening led to an enhanced coefficient of friction till stabilization occurred after approximately 150 m of sliding distance.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| 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".