Tailoring the solid oxide fuel cell anode support composition and microstructure for low‐temperature applications
Bibliographic record
Abstract
Abstract In this research, the performance of a tubular fuel cell based on a nickel oxide–yttria‐stabilized zirconia (Ni‐YSZ) anode support containing 90 wt% NiO ≈ 82 vol.% of Ni (Ni82) is compared with a cell containing the conventional Ni‐YSZ support with 50 vol.% Ni. A Ni‐YSZ buffer layer with a tailored microstructure was added to the Ni82 support layer to provide intermediate porosity and to reduce the thermal expansion mismatch with the anode functional layer. Both cells were tested using infiltrated Nd 2 NiO 4+δ cathodes. High peak power densities of 790 and 478 mW/cm 2 were achieved at 600 and 550°C, respectively, for the Ni82 cell which was 25% and 87% higher than the performances for the conventional cell at respective temperatures. In addition, no degradation was found during four redox cycles at 550°C, making this support an attractive candidate for low‐temperature solid oxide fuel cell applications.
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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 | 0.001 |
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".