O<sub>2</sub> Reduction Mechanism on Non-Noble Metal Catalysts for PEM Fuel Cells. Part I: Experimental Rates of O<sub>2</sub> Electroreduction, H<sub>2</sub>O<sub>2</sub> Electroreduction, and H<sub>2</sub>O<sub>2</sub> Disproportionation
Bibliographic record
Abstract
One Fe/N/C cathode electrocatalyst for PEM fuel cells with a nominal loading of 0.2 wt % Fe was prepared by heat-treating at 950 °C in NH 3 a nonmicroporous furnace carbon black impregnated with iron acetate. O 2 reduction reaction (ORR) occurs on this catalyst with an apparent 4e transfer, while H 2 O 2 electroreduction is sluggish, thereby minimizing the importance of the peroxide electroreduction pathway. It is also shown that H 2 O 2 disproportionates only slowly into H 2 O and 1 / 2 O 2 on this Fe/N/C catalyst. Therefore, the electrochemical−chemical pathway of O 2 to H 2 O 2 followed by H 2 O 2 disproportionation is minor during ORR. It is concluded that the present Fe/N/C catalyst reduces O 2 to water following mainly a direct 4e pathway. It is also noticed that the initial porosity of the carbon support may drastically influence the ORR mechanism. The same investigation was extended to other M/N/C electrocatalysts, where M = Cr, Mn, Co, Ni, and Cu, prepared according to the same procedure as used for Fe/N/C. A correlation was found between the ORR activity and the activity for H 2 O 2 disproportionation. This is explained by the occurrence of a common rate-limiting intermediate for the two reactions: the oxo-ferryl-like cation radical.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".