Stabilization of Ni-YSZ Nanocomposite Anodes by Deposition of a Thin YSZ Overlayer
Bibliographic record
Abstract
Lowering the operating temperatures of solid oxide fuel cells (SOFCs) to below 600 °C is projected to enhance the long term stability of these devices by slowing down thermally induced microstructural changes in the electrodes. To minimize the electrode resistance caused by the lowered operating temperatures, the fabrication of nanocomposite Ni-YSZ thin film electrodes with high triple phase boundary (tpb) lengths is a possible approach. However, these nanocomposite electrodes will still undergo microstructural changes that could cause performance degradation. Here, it is shown that the long-term stability of nanocomposite Ni-YSZ anodes can be enhanced by the deposition of a thin, poroous, YSZ coating on the outer surface of the Ni-YSZ electrodes, preventing Ni diffusion out of the pores followed by Ni particle formation. A degradation rate of 0.072 Ω·cm 2 /hour was observed for the standard Ni-YSZ nanocomposite thin film anode, whereas a much lower degradation rate of 0.011 Ω·cm 2 /hour was achieved after applying the YSZ coating.
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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 | 0.000 | 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) | 0.000 | 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".