Effect of pre‐oxidation on coke formation and metal dusting of electroplated Ni<sub>3</sub>Al–CeO<sub>2</sub>‐based coatings in CO–H<sub>2</sub>–H<sub>2</sub>O
Bibliographic record
Abstract
Abstract Pre‐oxidation was introduced to improve the resistance of electroplated pure, 5 µm CeO 2 ‐dispersed, and 9–15 nm CeO 2 ‐dispersed Ni 3 Al coatings to coke formation and metal dusting in 24.4%CO–73.3%H 2 –2.3%H 2 O at 650 °C. Coke formation and metal dusting of pre‐oxidized Ni 3 Al‐based coatings were retarded up to 200 h owing to a thin Al 2 O 3 scale induced during pre‐oxidation. The long‐term effectiveness of pre‐oxidation nonetheless depended on the integrity of Al 2 O 3 scale. The pure Ni 3 Al coating suffered severe spallation after pre‐oxidation and thereby showed the worst long‐term resistance. Two pre‐treated 9–15 nm CeO 2 ‐dispersed Ni 3 Al coatings exhibited the best long‐term resistance to carbon attack because nano‐CeO 2 particles maintained a full coverage of Al 2 O 3 scale on the coatings. Two 5 µm CeO 2 ‐dispersed Ni 3 Al coatings showed significant spallation after pre‐oxidation because of an overdoping effect and experienced coke formation and metal dusting during long‐term exposure.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".