Understanding the Activity Trade-Off between Tetrapyrrolic Fe-NCs and Co-NCs in the Alkaline Oxygen Reduction Reaction
Bibliographic record
Abstract
A water-free ionothermal synthesis of porous magnesium-imprinted nitrogen-doped carbon (Mg–NC) materials is introduced to prepare a platform material to investigate electrocatalytic structure-performance relations. Atomically dispersed Co- and Fe-NCs isomorphic to the pristine Mg-NCs are prepared by ion-exchange reactions. The current Mg-templating strategy enables relatively high pyrolysis product yields of up to 50 wt% and resultant Fe-NC and Co-NC catalysts contain high and comparable active metal loading of up to 2.52 wt% Fe and 2.29 wt% Co, respectively. A combination of X-ray spectroscopies with DFT studies reveals a tetrapyrrolic structure of the coordination sites, originating from a pyrolytic magnesium template ion reaction within the ionothermal synthesis. Two sets of highly active isomorphic tetrapyrrolic Fe-NCs and Co-NCs are utilized to understand the differences in intrinsic electrocatalytic performance of Co-NCs and Fe-NCs towards the alkaline oxygen reduction reaction (ORR). Despite their superior valence electronic properties to facilitate the initial outer-sphere electron transfer to O2, Co-NCs show significantly lower performance than Fe-NC with comparable loading. Although the generally discussed weaker binding of peroxide intermediates to CoN4 sites compared to FeN4 sites is evident, experimental and theoretical investigation reveal that it is the underlying peroxide oxidation activity that suppresses the oxygen reduction activity of M-NCs. The high peroxide oxidation activity of Co-NCs explains their reduced alkaline ORR relative to Fe-NCs, shedding light on the understated significance of controlling peroxide chemistry for the optimizing cathodic performance.
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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 | 0.000 | 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".