Promoting Selective Electrochemical CO2 Reduction Under Unconventionally Acidic Conditions Through Secondary Coordination Sphere Positioning
Bibliographic record
Abstract
While several studies have investigated the effects of protic secondary coordination sphere (SCS) groups on the kinetics of iron tetraphenylporphyrin (FeTPP) catalysed CO2 reduction, few have examined how a protic SCS might alter reaction selectivity. Under mildly acidic conditions, FeTPP‐based catalysts are selective towards the 2e–/2H+ reduction of CO2 to CO; however, in the presence of more acidic proton donors, indiscriminate proton transfers often result in parasitic H2 evolution. This report investigates how SCS amide positioning alters CO versus H2 selectivity during CO2 reduction with a series of four FeTPP isomers bearing SCS amides at varying positions around the porphyrin core: NH donors are placed at either the meta or ortho position of the meso aryl porphyrin ring, as well as proximal (closer) or distal (farther away) to the porphyrin plane. In the presence of a conventional, weakly acidic proton source (phenol; pKa = 29.2 in MeCN), all isomers display the expected high Faradaic efficiency (FE) towards CO (FECO = 67–85%) along with minimal H2 evolution (FEH2 = 3–13%). With a significantly stronger acid (3,5-bis(trifluoromethyl) phenol; pKa = 23.8 in MeCN), H2 becomes the major product when using the ortho-distal or both meta isomers (FEH2 = 45–65%) as well as unfunctionalized FeTPP (FEH2 = 78%). Importantly, the ortho-proximal isomer shows dramatically rescued CO selectivity under these unconventionally acidic conditions (FECO = 83 ± 4%). These results show how proper SCS placement impacts reaction selectivity during CO2 reduction, particularly with respect to minimizing indiscriminate proton transfers that lead to undesirable reactivity.
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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".