CO<sub>2</sub> Electroreduction to Methane at Production Rates Exceeding 100 mA/cm<sup>2</sup>
Bibliographic record
Abstract
The electrochemical reduction of CO 2 to methane is a promising method to store intermittent renewable energy. Previous research reporting high methane selectivity has relied on H-cells, and total current densities have therefore resided below 50 mA/cm 2, insufficient for industrial applications. Here, we increase the methane production rate by modifying the system so that it functions efficiently in a flow cell configuration. We investigate the impact of the local environment on methane selectivity in flow cells by tuning the choice of electrolyte cation, catalyst thickness, and local pH. We achieve a methane selectivity of 48% ± 4% with a partial current density of 120 ± 10 mA/cm 2, representing a cathodic energy efficiency of 23%. We showcase a stable operation for 14 h.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".