Degradation of La<sub>0.6</sub>Sr<sub>0.4</sub>Co<sub>0.2</sub>Fe<sub>0.8</sub>O<sub>3–</sub><i><sub>δ</sub></i>–Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>1.9</sub> Cathodes on Coated and Uncoated Porous Metal Supports
Bibliographic record
Abstract
Abstract The degradation of composite LSCF‐SDC cathodes on porous 430 stainless steel supports was investigated. Two degradation mechanisms were observed: a multi‐layer oxide scale, believed to consist of Cr2O3 and SrCrO4, formed at the support‐cathode interface, and small amounts of chromium were detected within the cathodes. To reduce degradation, La2O3 and Y2O3 reactive element oxide coatings were deposited on the internal pore surfaces of the metal supports. The reactive element oxide coatings reduced the amount of volatile chromium that deposited in the cathodes. As a result, the degradation rates of the cathodes on coated supports were significantly lower than the degradation rates of cathodes made on uncoated metal supports. In cathode symmetrical cells, polarization resistance degradation rates as low as 2.56 × 10−6 Ω cm2 h−1 were observed over 100 hours on coated metal supports, compared to an average of 1.23 × 10−4 Ω cm2 h−1 on uncoated supports.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".