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 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".