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 Nd2NiO4+δ cathodes. High peak power densities of 790 and 478 mW/cm2 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 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) | 0.000 | 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".