Enhancing the Stability of Infiltrated Ni/YSZ Anodes
Bibliographic record
Abstract
One possible solution to the redox cycling problem in Ni-based anodes is the fabrication of a pre-sintered porous electrolyte matrix, followed by infiltration of 10-20 vol% of a Ni-based catalyst into this scaffold. However, this can lead to instability as a result of sintering of the infiltrated phase at SOFC working temperatures. In this study, various Ni-containing solutions were infiltrated into a symmetrical tubular half-cell, with electrochemical impedance spectroscopy (EIS) and electron microscopy imaging used to determine the long term stability of the cells. It was found that the amount of infiltrated Ni has a significant impact on the long term stability of the Ni/YSZ anodes, explained by the better connectivity between Ni particles when there is more Ni present. It was also demonstrated that high temperature treatment of the infiltrated Ni/YSZ anodes just after the first few infiltrations, followed by several further Ni infiltration steps, has a significant effect not only on the stability of the anode at 800 o C, but also on the anode performance. As the YSZ backbone has the ability to dissolve NiO at higher temperatures, the dissolved NiO can be ex-soluted in the form of at least partially inter-connected nano-sized Ni particles at cell working temperatures under a reducing atmosphere.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".