Microstructural characterization of ZrB2–SiC–Si–MoSi2–WC coatings applied by SPS on graphite substrate
Bibliographic record
Abstract
The aim of this research was to apply a protective composite coating made of ultra-high temperature ceramics (UHTCs) on the graphite substrates. The spark plasma sintering (SPS) method was used to apply this coating on the graphite substrate. First, efforts were made to choose the right chemical composition for the composite material of the coating and the sintering conditions (temperature, pressure, and holding time) for applying the coating. Then, single-layer coatings with the basic composition of ZrB2–SiC–Si with WC and MoSi2 additives in equal amounts of 1.25 and 3.75 vol% of each were successfully applied on the graphite substrates under sintering conditions of 1875±25 °C final temperature, 10 MPa initial pressure, 25 MPa final pressure and 5 min holding time. The presence of the Si element in the basic composition of these coatings, in addition to helping to form an intermediate diffusion layer at the interface between the composite coating and the graphite substrate, caused the strengthening of the joining despite the difference in the coefficient of thermal expansion between the graphite and the composite coating.
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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".