Distortions in Electrochemical Impedance Spectroscopy Measurements Using 3‐Electrode Methods in SOFC. II. Effect of Electrode Activity and Relaxation Times
Bibliographic record
Abstract
Abstract The 3‐electrode configuration is commonly applied to quantify the overpotential of anodes or cathodes in solid‐oxide fuel cells (SOFC). In this type of set‐up, a reference electrode (RE) is used to isolate the potential loss of one electrode from that of the entire cell; however, erroneous results can be obtained whenever the RE does not precisely separate the potential drop between the two active electrodes. In this study, we present the results of a theoretical and experimental analysis focused on verifying the effectiveness of the 3‐electrode configuration in electrochemical impedance spectroscopy measurements for the kinetic characterisation of SOFC electrode reactions. The focus of this paper is on the distortion of impedance measurements caused by differences in the area‐specific polarisation resistance and impedance time constants of the working and counter electrodes. The results obtained numerically and experimentally, both for planar and tubular SOFC cell geometries, prove the reliability of the theoretical model used. From the systematic simulation presented here and in our previous work, it was possible to formulate general guidelines for the design of 3‐electrode experimental SOFC. The theoretical model used here can also be used to verify the consistency of EIS measurements obtained with thin planar cells.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".