Development of Bi‐layer Metal Substrate Architectures for Suspension Plasma Sprayed Solid Oxide Fuel Cells
Bibliographic record
Abstract
Abstract Metal‐supported solid oxide fuel cells have several advantages, which could potentially increase the overall competitiveness of the technology, compared to their cermet‐supported counterparts. However, surface imperfections and rapid oxidation of the metal supports at operating temperatures are factors that affect the electrochemical performance and durability of the cells. In this study, we have developed bi‐layer metal supports consisting of a thin, finely structured top layer and a thicker, more coarsely structured bottom layer. The fine top layer has small surface pore sizes which facilitate the deposition of defect‐free electrolyte layers, while the coarse layer provides greater open porosity and larger pore sizes to facilitate mass transport and to decrease the rate of oxidation. An open circuit voltage (OCV) as high as 1.105 V at 750 °C in 3% humidified hydrogen is reported in this study, which deviates from the Nernst potential by only 5 mV. This result shows that the bi‐layer support has the potential to minimize electrode and electrolyte defects, which are known to be detrimental to cell performance. In addition, the bi‐layer supports show better oxidation resistance compared to benchmark finely‐structured single‐layer supports fabricated in this study for comparison.
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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".