Influence of post-spraying heat treatments on the oxidation and cracking behaviour of thermal-sprayed thermal barrier coatings
Bibliographic record
Abstract
The durability of a thermal barrier coating (TBC) system is dominated by fracture near the interface between the ceramic topcoat and metallic bond coat, where a layer of thermally grown oxide (TGO) would form during service exposure. Even though the formation of a continuous alumina scale would help to protect the bond coat from further oxidation, the spontaneous formation of other mixed oxides such as spinel and nickel oxide are believed to be detrimental to TBC durability. The formation of such detrimental oxides may promote crack nucleation and accelerate crack propagation during thermal exposure, leading to premature TBC failure. The present study shows that post-spraying heat treatment in low-pressure oxygen environments can promote the formation of a thin alumina scale that suppresses the spontaneous formation of detrimental oxides during subsequent thermal exposure. This results in an improved oxidation resistance of the bond coat and, hence, it slows down crack propagation in the thermal-spray TBC systems. The relationship between the oxide scale growth and crack propagation is also established through extensive metallurgical examination, which serves as the basis for a TBC life prediction model.
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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 | 0.001 |
| 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".