Isolated Cu-Sn diatomic sites for enhanced electroreduction of CO2 to CO
Why this work is in the frame
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Bibliographic record
Abstract
Electrochemical CO2 reduction reaction (CO2RR) to high-value product, CO, not only provides a key feedstock for the well-established Fischer—Tropsch process but also mitigates the greenhouse effect. However, it suffers from sluggish reaction kinetics, competitive hydrogen evolution reaction, and low selectivity. Herein, we report non-precious Cu-Sn diatomic sites anchored on nitrogen-doped porous carbon (CuSn/NPC) as an efficient catalyst for CO2RR to CO. The catalyst exhibits outstanding selectivity with CO Faradaic efficiency (FE) up to 99.1%, much higher than those of individual Cu (66.2%) and Sn (51.3%) single-atom catalysts. Moreover, high stability is confirmed by consecutive 24 h electrolysis with high selectivity from CO2 to CO. Theoretical calculations reveal an obvious activation of CO2 with weakened C—O bonds and distorted CO2 configuration upon chemisorption on the CuSn/NPC catalyst. It is also suggested CuSn/NPC is more selective for the CO2RR with dominant CO production during the electrolysis, rather than the competing hydrogen evolution reaction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 it