Electrochemical Pressure Impedance Spectroscopy for Polymer Electrolyte Fuel Cells via Back-Pressure Control
Bibliographic record
Abstract
Electrochemical pressure impedance spectroscopy (EPIS) analyses the voltage response of a polymer electrolyte fuel cell (PEFC) as a function of an applied pressure signal in the frequency domain. EPIS is similar to electrochemical impedance spectroscopy (EIS) and its development was inspired by the diagnostic capabilities of the latter. The EPIS introduced in this work modulates the cathode pressure of a PEFC with a sinusoidal signal through the use of a back-pressure controller, and monitors the cell voltage while holding the cell at a constant current. A sinusoidal pressure wave propagates along the flow field channels because of this pressure modulation. This pressure wave impacts local reaction rates and transport properties in the cathode, resulting in a sinusoidal voltage response. The amplitude ratio and phase difference between these two sinusoidal waves entail diagnostic information on processes that take place within the PEFC. To demonstrate the utility of the EPIS technique, experiments have been carried out to measure and analyze the frequency response of PEFCs with two different flow fields. A parametric study has been conducted to characterize the effect of pressure oscillation amplitude, load, oxygen concentration, oxygen stoichiometry and cathode gas flow rate on the EPIS signal.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".