Fe-Based Catalysts for Oxygen Reduction in PEM Fuel Cells
Bibliographic record
Abstract
Fe-based catalysts for reduction have been prepared on four carbon supports (Vulcan, Black Pearl, Norit, and a developmental carbon, RC2, from Sid Richardson Carbon Corp.). Four preparation procedures have been used with each carbon support and the catalytic activities for the reduction of oxygen in pH 1, and in polymer electrolyte membrane fuel cell tests are compared for all the catalysts, which are nominally loaded with 0.2 wt % Fe, using acetate as Fe precursor. The catalytic activity of these Fe-based catalysts greatly depends upon the chosen carbon support and also upon the preparation procedure used. The results are rationalized in terms of N content at the surface of the catalysts; the larger the N content, the better the catalytic activity. The best catalysts are obtained after refluxing either RC2 or Norit in before adsorbing iron acetate on the oxidized carbon supports and heat-treating the resulting materials at 900°C in an atmosphere containing The surface nitrogen content of these catalysts, measured by XPS, is 2.5 and 4.1 atom %, respectively. For the Fe-based catalyst prepared on Norit and tested in fuel cell, the mass activity at low current regime, expressed in A/mg Fe, is only slightly lower than the A/mg Pt recorded for a state-of-the-art, Pt-based membrane electrode assembly. © 2004 The Electrochemical Society. All rights reserved.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".