Temperature Sensitivity Analysis of Electrochemical Impedance Spectroscopy Results in PEM Fuel Cells
Bibliographic record
Abstract
The proton exchange membrane fuel cell (PEMFC) is a promising substitute for classic energy converter machines. However, there are still concerns regarding reliability and durability of PEMFCs, and hence, various modeling methods have been employed. One of the effective methods used for analysis and diagnosis of the fuel cell and other electrochemistry systems is Electrochemical Impedance Spectroscopy (EIS) which has been well established due to its high speed and precision. In this paper, the temperature sensitivity of the EIS results at different current densities obtained for a high temperature PEMFC are studied using electrochemical impedances reported in the literature. The magnitude of different elements in the proposed equivalent circuit for different temperatures and current densities, and root mean squares of deviation of various measurements are extracted. Then, the significance of the variations for different temperatures is examined via t-test. Finally, the minimum temperature change at different currents that can be captured by EIS is determined considering the root mean squares of measured values.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".