Metal-supported Solid Oxide Fuel Cell Operated at 400~600{degree sign}C
Bibliographic record
Abstract
Metal-supported SOFCs potentially offer many advantages compared to conventional technology, such as low operating temperatures, reduced cost, and increased reliability. They are also a promising choice for applications that require quick start-up, good stability against thermal cycles and mechanical shock resistance such as Auxiliary Power Units (APU) for the automotive industry. The National Research Council of Canada's Institute for Fuel Cell Innovation (NRC-IFCI) has been working on the development of metal supported SOFCs since 2004. In this paper, a metal-supported SOFC with a samarium doped ceria (SDC)/scandia-stabilized zirconia (ScSZ) bilayer electrolyte was fabricated by a combination of pulsed laser deposition (PLD) and wet chemistry processing. The cell performance and aging characteristics were analyzed by AC impedance spectroscopy and current-voltage measurements during operation in the temperature range from 400oC to 600oC. The power generation characteristics at low temperatures of this metal- supported SOFC will be beneficial for quick start-up and is expected to alleviate the performance deterioration. These results at such an early stage of research is very promising for the future development of this technology.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".