Promoting CO2 methanation via ligand-stabilized metal oxide clusters as hydrogen-donating motifs
Bibliographic record
Abstract
Electroreduction uses renewable energy to upgrade carbon dioxide to value-added chemicals and fuels. Renewable methane synthesized using such a route stands to be readily deployed using existing infrastructure for the distribution and utilization of natural gas. Here we design a suite of ligand-stabilized metal oxide clusters and find that these modulate carbon dioxide reduction pathways on a copper catalyst, enabling thereby a record activity for methane electroproduction. Density functional theory calculations show adsorbed hydrogen donation from clusters to copper active sites for the *CO hydrogenation pathway towards *CHO. We promote this effect via control over cluster size and composition and demonstrate the effect on metal oxides including cobalt(II), molybdenum(VI), tungsten(VI), nickel(II) and palladium(II) oxides. We report a carbon dioxide-to-methane faradaic efficiency of 60% at a partial current density to methane of 135 milliampere per square centimetre. We showcase operation over 18 h that retains a faradaic efficiency exceeding 55%.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".