Solid oxide cell electrolytes deposited by atmospheric suspension plasma spraying at high velocity and high temperature
Bibliographic record
Abstract
Abstract Metal‐supported solid oxide cells with Yttria‐stabilized zirconia (YSZ) electrolytes fabricated by atmospheric plasma spraying are routinely found to have open‐circuit voltages (OCVs) below the Nernst potential due to gas crossover and combustion resulting from electrolyte defects. To improve splat bonding and reduce coating defects, YSZ electrolytes were fabricated here at >800°C substrate temperatures and torch‐substrate relative velocities of 4 and 12 m/s by atmospheric suspension plasma spraying. Electrolyte microstructures appeared dense, with porosities estimated to be approximately 2.2–3.5 vol%. Minimal segmentation cracking was observed on samples fabricated at 12 m/s. The full cells that were electrochemically tested had permeabilities in the range of 4–6 × 10−19 m2, and the maximum recorded OCV was ∼26 mV below the Nernst potential for 750°C. Potential performance gains from YSZ deposition at substrate temperatures >800°C may have been masked by poor substrate‐fuel electrode contact. Using electrochemical impedance spectroscopy, it was found that the ohmic and polarization resistances decreased and increased, respectively, over time. The calculated distribution of relaxation times of the tested cells, together with observations from the literature, were employed to identify possible cell degradation mechanisms observed during short‐term durability testing.
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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".