Enhanced Acidic CO <sub>2</sub> ‐to‐C <sub>2+</sub> Reduction via Ionic Liquid Layer Modification
Bibliographic record
Abstract
Abstract Acidic CO 2 electroreduction reaction (CO 2 RR) garners significant attention as a promising approach for cutting carbon density, as it effectively mitigates CO 2 loss by suppressing carbonate species formation. Unfortunately, achieving efficient multi‐carbon products (C 2+ ) production in acidic media remains challenging due to two main limitations: weak CO adsorption on Cu sites and competitive H* adsorption caused by the high concentration protons (H + ). To overcome these challenges, a cation‐anion‐modification strategy is proposed using an ionic liquid layer—1‐Propyl‐3‐methylimidazolium bis(trifluoromethylsulfonyl)imide ([PMIM][NTf 2 ])—on Cu surface. Density functional theory calculations predict that PMIM + cation strengthens *CO adsorption through quasi‐hydrogen bonding, while NTf 2 − anion creates a hydrophobic environment, effectively reducing H* coverage and promoting *CO adsorption. Resistance tests demonstrate that [PMIM][NTf 2 ] modification effectively reduced proton diffusion. Attenuated total reflection infrared spectroscopy (ATR‐IR) confirmed the reinforcement of *CO adsorption on the modified Cu surface. As a result, the [PMIM][NTf 2 ] modified Cu catalyst achieved a remarkable partial current density of ≈640 mA cm −2 for C 2+ products, with exceptional faradaic efficiency of 80.1% and durability of ≈20 h at a partial current density exceeding 500 mA cm −2 in a flow cell. This study highlights the potential of cation‐anion modification strategies for significantly enhancing CO 2 RR in acidic media.
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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 | 0.001 |
| 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 | 0.001 |
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 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".