Modulating Cation and Water Transports for Enhanced CO Electrolysis via Ionomer Coating
Bibliographic record
Abstract
Abstract Electrification of the chemical industry has been considered an enabler for energy transition on a massive scale. In this context, carbon monoxide electroreduction (COR) to produce multi‐carbon (C 2+ ) products is considered one of the forefront emerging technologies. The key challenge in COR comes from the excessive cation crossover to the cathode via electromigration and water diffusion, which limits CO availability and impedes product selectivity. Commercial anion exchange membrane (AEM) suppresses the electromigration of cations, however, suffers from water diffusion which facilitates cation crossover. Here, we tackled these problems emerging from cation crossover and water diffusion by directly depositing an ultrathin Nafion ionomer on the cathode (sputtered Cu) surface. Our approach enables full‐cell energy efficiency of 21 % for converting CO into ethylene (C 2 H 4 ) at 100 mA/cm 2 with over 200 hours of stable operation. We also exhibited record high energy efficiency for ethanol (C 2 H 5 OH) production with CO‐to‐C 2 H 5 OH electrolysis efficiency of 17 %. This approach to directly depositing ultrathin ionomer on the cathode to enhance system performance may benefit other electrochemical systems to overcome challenges associated with scalability, stability, and efficiency to produce high‐value chemicals.
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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 | 0.000 |
| 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) | 0.000 | 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".