Heterogeneous Aqueous CO2 Reduction Using a Pyrene-Modified Rhenium(I) Diimine Complex
Bibliographic record
Abstract
The development of molecular catalysts and materials that can convert CO2 into a value-added product is a great chemical challenge.Molecular catalysts set benchmarks in catalyst investigation and design, but incorporation of these catalysts into solid-state materials, and optimization of the electrochemical operating conditions, is still needed.For example, rhenium(I) diimine catalysts show almost quantitative selectivity for conversion of CO2 to CO in acetonitrile, but modification of diimine backbones can be challenging if the goal is to incorporate such molecules into materials.Presented here is a Re(I) complex with a 2-(2´-quinolyl)benzimidazole (QuBIm-H) ligand, where N-alkylation with a pyrene derivative allows access to a catalyst that can be adsorbed onto electrodes for aqueous CO2 reduction chemistry.The Re(I) catalysts are inactive for homogeneous CO2 reduction reaction in MeCN.However, when adsorbed on edge plane graphite, the same complexes show good activity for heterogeneous aqueous CO2 reduction with 90% selectivity for CO.Comparative electrochemical studies between covalent and non-covalent modification of the graphite surfaces also were carried out for related Re(I)-tricarbonyl complexes.
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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".