Changing the Selectivity of O2 Reduction Catalysis with One Ligand Heteroatom
Bibliographic record
Abstract
The development of catalytic systems that selectively reduce O2 to water is needed to continue the advancement of fuel cell technologies.As an alternative to platinum catalysts, derivatives of iron (Fe) and cobalt (Co) porphyrin molecular catalysts provide one benchmark for catalyst design, but incorporation of these catalysts into heterogeneous platforms remains a challenge.Co-porphyrins can be heterogeneous O2 reduction catalysts when immobilized on to edge plane graphite (EPG) electrodes, but their selectivity for the desired 4-electron reduction of O2 to H2O is often poor.Herein, we demonstrate substantial improvements in the O2 reduction selectivity for a Coporphyrin by incorporating a 2-pyridyl group at one of the meso-positions of a Cotetraarylporphyrin (cobalt(II) 5-(2-pyridyl)-10,15,20-triphenylporphyrin, CoTPPy).The properties of CoTPPy immobilized on EPG were investigated using cyclic voltammetry, rotating disk and rotating ring-disk electrochemistry.The presence of a single 2-pyridyl group in the CoTPPy gives rise to the 4-electron reduction of O2, as opposed to the 2-electron reduction commonly associated with cobalt porphyrins.Detailed electrochemical studies of CoTPPy and related Co and Fe porphyrins are described.Use of Co instead of Fe improves overpotentials by over 200 mV with a factor of two increase in maximum turnover frequency (TOFmax).This work demonstrates that a simple change in catalyst structure can dramatically change the selectivity for O2 reduction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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".