Electrochemical impedance study of anode CO-poisoning in PEM fuel cells
Bibliographic record
Abstract
Polymer electrolyte membrane (PEM) fuel cells operate efficiently when using pure hydrogen, but poorly when using hydrogen derived from hydrocarbon or methanol processing. The reason for this phenomenon is the capacity of carbon monoxide )CO) present in the reformed gas to act as a poison of the platinum electrocatalyst in the anode. The objective of this paper is to examine data on CO-poisoned anodes by using electrochemical impedance spectroscopy (EIS), a technique which was demonstrated to provide some interesting conclusions in the diagnostics and characterization of entire fuel cells, and particularly in determining the cathode performance, leading to a new criterion for evaluating the CO tolerance of electrocatalysts. EIS spectra on Pt and Pt/Ru gas diffusion electrodes are presented and compared at various potentials, in order to furnish new criteria for characterizing the CO tolerance of electrocatalysts. Attention is focused on EIS pattern as a function of CO concentration, catalyst loading and temperature; these are discussed comparatively for Pt and Pt/Ru. While Pt/Ru gas diffusion electrodes show clearly a much lower impedance, hence better activity, than Pt-based electrodes, there is no indication that the appearance of the semi-inductive behaviour of Pt accounts for CO removal, i.e. the better activity of the Pt/Ru in the low overpotential range is more likely to be due to the decrease of CO adsorption by site exclusion than to the appearance of CO oxidative removal at the lower potential. In effect, the superior activity of Pt/Ru is due to a larger ratio between the rates of CO oxidation and re-adsorption and not to a larger rate of oxidation itself. 27 refs., 2 tabs., 11 figs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".