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 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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".