Modifying the Rate of Rhenium(Diimine)-Mediated Electrochemical Carbon Dioxide Reduction via the Addition of a Redox-Active Functional Group Near the Active Site
Bibliographic record
Abstract
The development of electrocatalysts that efficiently valorize carbon dioxide (CO 2 ) is of ongoing interest. To that end, there is interest in the advancement of molecular catalysts that can promote reactions that address reaction bottlenecks. Examples of emerging catalyst designs include ligands with ancillary groups that support proton transfer reactions or ligands with charged groups that promote electrostatic interactions that facilitate key reaction steps. Such designs have considerably improved CO 2 reduction rates with respect to unmodified parent complexes. However, examples where the ligand framework could provide more than one catalysis-assisting function are rare. Herein, we use a (diimine)Re(I)- fac (CO) 3 complex with an N -methylated terpyridine ligand to demonstrate that the placement of a cationic and redox-active group proximal to the Re active sites can improve CO 2 reduction rates. We observe a substantial improvement in observed rate constants with respect to the unmethylated terpy complex. However, the role of the methylpyridinium group is not as simple as pure redox mediation or electrostatic effects. Density functional calculations support the idea that both the redox reactivity of the entire ligand and the presence of only partial positive charge near the Re site can contribute to the observed CO 2 reduction properties. The results are an example of how ligand designs that incorporate combinations of ancillary groups with different properties can be used to promote electrocatalytic reactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".