Impact of Nonuniform Potential in SOFC Composite Cathodes on the Determination of Electrochemical Kinetic Parameters
Bibliographic record
Abstract
Engineering of porous solid oxide fuel cell (SOFC) composite cathodes comprising a mixture of electrocatalyst and ionic conductor requires the knowledge of electrochemical kinetic parameters such as the reaction order and the charge-transfer coefficients. Conventional dc techniques are commonly employed in electrochemical measurements for composite cathodes. The results are often analyzed in terms of the low-or high-field approximations of the Butler–Volmer equation, which is based on the assumption that no potential or overpotential gradients exist within the electrode. In this study, numerical simulation of lanthanum strontium manganate–yttria-stabilized zirconia composite cathode was performed with an assumed oxygen reduction reaction mechanism and corresponding electrochemical kinetic parameters. The simulation results indicated that for composite cathodes significant gradients in the overpotential exist. The apparent reaction order and apparent charge-transfer coefficients, derived on the basis of nominal overpotential and net current, the two quantities that are typically accessible experimentally, were significantly different than the actual kinetic parameters used in the simulation. The extent of the variation between the actual and apparent electrochemical kinetics parameters was found to be dependent on the thickness and microstructure of the composite cathode. Simulation of conventional cathodes, which had no potential gradients within the bulk of the cathode, showed no errors.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".