Double Doped Ceria Electrolyte Synthesized by Solution Plasma Spraying with Induction Plasma Technology
Bibliographic record
Abstract
Abstract In the continuing progress of fuel cell technology, CeO2 double doped electrolytes appears to be promising for lowering the SOFC's working temperatures. Ceria electrolytes have better ionic conductivities than YSZ but, at low oxygen partial pressures, the chemical reduction of ceria leads to increasing electronic conduction. Double doping of the ceria increases the electrolytic conduction range without changing its conductivity. To avoid stress development within the ceria crystallographic structure, the dopants mix must have a mean ionic radius as close as possible to the critical ionic radius. Ceria electrolytes with various compositions and dopant concentrations are synthesized with a combinatorial chemistry approach. To synthesize new electrolytes, solution plasma spraying with nitrate salt precursor is used. The reaction is completed and nanocrystalline thin layers of ceramic are formed in the plasma. Comparative studies of plasma spraying techniques, with YSZ powder plasma spraying as electrolyte reference, were performed. Also, comparative impedance spectroscopy measurements are to be performed to validate the double doping hypothesis and thence to identify the best electrolytes in the suite of over 300 new materials.
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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 | 0.001 |
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".