Aqueous CO <sub>2</sub> Reduction by a Re(bipyridine)-polypyrrole Film Deposited on Colloid-Imprinted Carbon
Bibliographic record
Abstract
Herein, we report a [Re(bipyridine)]-carbon hybrid material for efficient and selective CO2 to CO conversion in water. The Re catalyst was incorporated into a nanoporous colloid-imprinted carbon (CIC) powder by an electrochemical polymerization method. Uniform [Re(bipyridine)]-containing polymer films were formed on the carbon surface, where the catalyst-polymer loading could be controlled by varying the polymerization parameters. Thorough pre- and post-catalysis characterization confirmed the integrity of the [Re(bpy)] CO2 reduction catalyst. CIC|poly[Re] electrodes reduced CO2 to CO in 0.5 M CO2-saturated KHCO3 electrolyte solution at Eappl. = −0.66 V versus reversible hydrogen electrode (RHE) (η = 550 mV), with initial Faradaic efficiencies for CO formation (FECO) between 88 and 100%. Higher catalyst loadings generally yielded higher FECO and better long-term stability under catalytic conditions, producing CO and maintaining selectivity of above 70% for a period of at least 24 h for the hybrid material with the highest [Re(bipyridine)] polymer loading. While electrochemical analyses suggested some electron and mass transport issues on shorter timescales, these were not confirmed in long-term electrolysis. Our work highlights the great applicability of (electro)polymerization techniques in combination with nanoporous CIC to prepare hybrid materials for energy conversion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".