Controlling the Oxygen Reduction Selectivity of Asymmetric Cobalt Porphyrins by Using Local Electrostatic Interactions
Bibliographic record
Abstract
The development and improvement of electrocatalysts for the 4H + /4e – reduction of O 2 to H 2 O is an ongoing challenge. The addition of ancillary groups (e.g., hydrogen bonding, Brønsted acid/base) near the active site of metal-containing catalysts is an effective way to improve selectivity and kinetics of the oxygen reduction reaction (ORR). In this regard, iron porphyrins are among the most researched ORR catalysts. Closely related cobalt porphyrin ORR catalysts can function closer to the O 2 /H 2 O thermodynamic potential, but they tend to be less selective and follow a different mechanism than for the iron porphyrins. Herein, we explore strategies to extend the ideas about ancillary groups that have been developed for iron porphyrin ORR electrocatalysts to improve the performance of the corresponding cobalt complexes. We describe a series of porphyrin electrocatalysts that are modified versions of Co(5,10,15,20-tetraphenylporphyrin), where the 2-position of one of the phenyl groups contains -NH 2, -N(CH 3 ) 2, and -N(CH 3 ) 3 + . Investigations using cyclic voltammetry and hydrodynamic electrochemistry show that the presence of a cationic ancillary group gives rise to a catalyst that is selective for the conversion of O 2 to H 2 O across a wide pH range. In contrast, the other catalysts are selective for reduction of O 2 to H 2 O at pH 0, but produce H 2 O 2 at higher pH. The ORR rate (∼10 6 M –1 s –1 ) and selectivity of the -N(CH 3 ) 3 + -modified catalyst are invariant between pH 0 and 7. Quantum chemical calculations support the hypothesis that the enhancement of selectivity can be attributed to the distinct mechanism of O 2 reduction by Co-porphyrins. Specifically, the mechanism relies on anionic, peroxide-bound intermediates. While protic ancillary groups are important in the performance of iron porphyrin ORR catalysts, we suggest that electrostatic stabilizers of O 2 -bound intermediates are more crucial for cobalt porphyrin ORR catalysts.
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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".