On the Controversial Role of the Metal in Fe/N/C or Co/N/C Electrocatalysts for the Reduction of Oxygen in the Acidic Medium of PEM Fuel Cells
Bibliographic record
Abstract
The proton-exchange membrane hydrogen/air (PEM) fuel cell constitutes an efficient and environmentally-harmless alternative to the gasoline-dependent technology used today for transportation. However, the replacement of platinum-based catalysts, used at their electrodes and accounting for a large fraction of the fuel cell stack cost, is one of their challenges to reach full commercialization. Today, Fe/N/C-catalysts and perhaps also Co/N/C-catalysts obtained from the pyrolysis of molecular precursors are the most promising non-platinum-group-metal (non-PGM) catalysts for the electrochemical reduction of oxygen (air) to water in an acidic medium such as that of PEM fuel cells. Despite decades of research on Fe- (or Co) -based electrocatalysts for the oxygen reduction reaction (ORR), the role of the metal is still one that raises a great deal of controversy. Consequently, the nature of the catalytic site in these non-noble metal ORR catalysts is still a topic of debate. One camp within the scientific community believes that the metal is an integral and electrochemically active part of the catalytic site, while the other believes that the metal is merely a chemical catalyst for the formation of special oxygen-reducing N-doped carbon structures. After presenting the case for the importance of non-noble catalysts at the cathode of PEM fuel cells, we will introduce the three models of active sites that were advocated during the 1980’s by van Veen, Yeager, and Wiesener, and discuss how they have evolved, especially that of Yeager. Wiesener’s model will be analyzed in detail through the work of several research groups that have been staunch supporters. It will be shown that all the active sites proposed by van Veen, Yeager and Wiesener in the 1980’s, while different, are in fact simultaneously present in Fe- (or Co)-based catalysts active for ORR in acidic medium, except that their activity and relative population in these catalysts is different, depending on the choice of the metal precursor, nitrogen precursor, structural properties of the carbon support and the synthesis procedure. A good knowledge of the nature and structure of the catalytic sites is important to further improve catalyst activity and site stability, especially for the Fe/N/C cathode catalysts that lead to the highest power densities reported to date for non-PGM-based catalysts able to reduce oxygen at meaningful cell voltages in PEM fuel cells.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".