High-rate and selective conversion of CO2 from aqueous solutions to hydrocarbons
Bibliographic record
Abstract
Abstract Electrochemical carbon dioxide (CO 2 ) conversion to hydrocarbon fuels, such as methane (CH 4 ), offers a promising solution for the long-term and large-scale storage of renewable electricity. To enable this technology, CO 2 -to-CH 4 conversion must achieve high selectivity and energy efficiency at high currents. Here, we report an electrochemical conversion system that features proton-bicarbonate-CO 2 mass transport management coupled with an in-situ copper (Cu) activation strategy to achieve high CH 4 selectivity at high currents. We find that open matrix Cu electrodes sustain sufficient local CO 2 concentration by combining both dissolved CO 2 and in-situ generated CO 2 from the bicarbonate. In-situ Cu activation through alternating current operation renders and maintains the catalyst highly selective towards CH 4 . The combination of these strategies leads to CH 4 Faradaic efficiencies of over 70% in a wide current density range (100 – 750 mA cm -2 ) that is stable for at least 12 h at a current density of 500 mA cm -2 . The system also delivers a CH 4 concentration of 23.5% in the gas product stream.
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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) | 0.001 | 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".