Performance of Sm<sub>0.95</sub>Ce<sub>0.05</sub>Fe<sub>1-x</sub>Ni<sub>x</sub>O<sub>3-δ</sub>Perovskite as Anode Materials under Methane Fuel for Low Temperature Solid Oxide Fuel Cells (LT -SOFC)
Bibliographic record
Abstract
Sm0.95Ce0.05Fe1-xNixO3-δ (x=0-0.05) perovskite materials were investigated for their candidacy as anodes for Low temperature Solid Oxide Fuel Cell (LT-SOFC). Electrolyte supported button cells were made and tested with hydrogen and dry methane fuels. A three electrode geometry was used and electrochemical impedance measurements were carried out revealing that Ni doping does improve the performance of the resulting anodes as indicated by a decrease in charge transfer resistance values. The value of charge transfer resistance is lowest for x=0.03 (1.65 Ωcm2 at 600oC) and only light coking was observed.
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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".