Continuous electroproduction of formate via CO2 reduction on local symmetry-broken single-atom catalysts
Bibliographic record
Abstract
Abstract Atomic-level coordination engineering is an efficient strategy for tuning the catalytic performance of single-atom catalysts (SACs). However, their rational design has so far been plagued by the lack of a universal correlation between the coordination symmetry and catalytic properties. Herein, we synthesised planar-symmetry-broken CuN3 (PSB-CuN3) SACs through microwave heating for electrocatalytic CO2 reduction. Remarkably, the as-prepared catalysts exhibited a selectivity of 94.3% towards formate at −0.73 V vs. RHE, surpassing the symmetrical CuN4 catalyst (72.4% at −0.93 V vs. RHE). In a flow cell equipped with a PSB-CuN3 electrode, over 90% formate selectivity was maintained at an average current density of 94.4 mA cm−2 during 100 h operation. By combining definitive structural identification with operando X-ray spectroscopy and theoretical calculations, we revealed that the intrinsic local symmetry breaking from planar D4h configuration induces an unconventional dsp hybridisation, and thus a strong correlation between the catalytic activity and microenvironment of metal centre (i.e., coordination number and distortion), with high preference for formate production in CuN3 moiety. The finding opens an avenue for designing efficient SACs with specific local symmetries for selective electrocatalysis.
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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) | 0.000 | 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) | 0.001 | 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".