Electron-Reservoir Effect on a Perylene Diimide Tethered Rhenium Bipyridine Complex for CO2 Reduction
Bibliographic record
Abstract
Here we report on a molecular catalyst with a built-in electron-reservoir for enhanced CO2 conversion. The synthesis and characterization of this N-annulated perylene diimide (PDI) photosensitized Re(bpy) supramolecular dyad [Re(bpy-TAz-PDI)], as well as successful electro- and photocatalytic CO2-to-CO conversion, are detailed herein. Upon electrochemical reduction in the presence of CO2 and a proton source, Re(bpy-TAz-PDI) exhibited significant current enhancement, where the onset of electrocatalytic CO2 reduction for Re(bpy-TAz-PDI) occurred at a much less negative potential than standard Re(bpy) complexes. At an applied potential of -1.8 V vs. Fc+/0, 400 mV lower than the benchmark Re(dmbpy) catalyst, Re(bpy-TAz-PDI) was able to achieve the same catalytic activity (TONco = 24) and Faradaic efficiency (FE = 92 %) during controlled potential electrolysis (CPE) experiments. Through a combination of UV-visible-nearIR spectroelectrochemistry (SEC), FTIR SEC, and chemical reduction experiments, it was shown that the PDI-moiety served as an electron-reservoir for Re(bpy), thereby allowing catalytic activity at lower overpotentials. Density functional theory (DFT) studies probing the optimized geometries, frontier molecular orbitals, and spin-densities of various catalytic intermediates revealed that the geometric configuration of PDI, relative to the Re(bpy)-moiety, plays a critical role in accessing electrons from the electron-reservoir. The near identical performance of Re(bpy-TAz-PDI) at lower overpotentials relative to the benchmark Re(dmbpy) catalyst highlights the utility of organic chromophore electron-reservoirs as a method for lowering the required overpotential for CO2 conversion.
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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) | 0.002 | 0.001 |
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".