Fe-Based Catalyst for Oxygen Reduction: Functionalization of Carbon Black and Importance of the Microporosity
Bibliographic record
Abstract
Fe/N/C catalysts for the reduction of oxygen under the acidic conditions prevailing in PEM fuel cells have been prepared on two carbon black supports functionalized with N-bearing groups. Once loaded with 2000 ppm Fe, the functionalized carbons were pyrolyzed at 950ºC in Ar or NH3. The best catalysts were obtained under NH3. In addition to being a nitrogen precursor, NH3 also etches the carbon support increasing its microporosity. In NH3, the functionalities are rapidly etched away from the carbon support, but this once-functionalized carbon now reacts faster with NH3 than the pristine carbon. Therefore, the optimum microporosity necessary to produce the maximum catalytic activity is reached after a shorter pyrolysis time on the functionalized carbon supports than on the pristine carbons. However, the maximum catalytic activity for the oxygen reduction reaction (ORR) is the same for the once functionalized carbon as for the pristine one.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".