Active Sites and Stability Study of Fe/N/C Catalyst in PEMFCs: A Decade of Stunning Progress and the Remaining Challenges
Bibliographic record
Abstract
Over the past few decades, Fe/N/C, as the most promising platinum group metal (PGM) alternative, has provided a unique roadmap for developing proton exchange membrane fuel cells (PEMFCs) due to the low-cost and earth-abundant elements. However, the high-performance Fe/N/C catalysts always demonstrate poor stability, especially during real-world fuel cell operation, which has attracted increased attention in recent years. Great efforts have been devoted in the past decade to understanding active sites and their degradation mechanisms. Herein, we review the progress in the past decade in terms of active site identification and degradation phenomena/mechanisms of Fe/N/C catalysts, particularly in PEMFCs (rather than the conventional three-electrode system). Meanwhile, we also highlight the latest advances in improving the stability of PGM-free catalysts. At the end of this critical review, perspectives are provided to determine the potential strategies to further improve the activity and stability of Fe/N/C catalysts for PEMFCs.
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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 | 0.001 |
| 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".