Mechanical Behaviour of Air-Plasma Sprayed Functionally Graded YSZ-Mullite Environmental Barrier Coatings: A Study Via Instrumented Indentation
Bibliographic record
Abstract
Abstract Mullite (Al6Si2O13) is the basis of efficient environmental barrier coatings (EBCs) for protecting Si-based ceramic matrix composites (CMCs) selected to replace specific hot-section metallic components in advanced gas turbines. Furthermore, YSZ-mullite multilayer architectures with compositional grading between the bond coat and YSZ top coat were envisioned as solutions to ease their coefficient of thermal expansion (CTE) mismatch induced stress. Consequently, a proper understanding of the mechanical properties such as the elastic modulus, hardness or plastic/elastic recovery work serve for an efficient design of such refractory oxide multilayers. In this work, three different mullite powder morphologies (fused and crushed, spray-dried and freeze-granulated) were employed. Using depth-sensing indentation with loads in the range 100 – 500 mN, the role of the microstructure and morphology of the powder feedstock on the mechanical behaviour of air plasma sprayed mullite bond coats deposited on SiC Hexoloy substrates was investigated. Fully crystalline as-sprayed mullite coatings were engineered under controlled deposition conditions. Mechanical properties were measured for the as-sprayed coatings as well as for coatings heat-treated at 1300°C, in water vapour environment, for periods up to 500 h. Both E and H values of the coatings are found to be highly dependent on the morphology of the starting powders.
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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".