Photocatalytic asymmetric C-C coupling for CO2 reduction on dynamically reconstructed Ruδ+-O/Ru0-O sites
Bibliographic record
Abstract
Solar-driven CO2 reduction to value-added C2 chemicals is thermodynamically challenging due to multiple complicated steps. The design of active sites and structures for photocatalysts is necessary to improve solar energy efficiency. In this work, atomically dispersed Ru-O sites in RuxIn2-xO3 are constructed by interior lattice anchoring of Ru. This results in the dynamic reconstruction of Ruδ+-O/Ru0-O sites upon photoexcitation, which facilitates the CO2 activation, *CO intermediates adsorption, and C-C coupling as demonstrated by varied in situ techniques. A SiO2 core in RuxIn2-xO3/SiO2 construction further enhances the solar energy utilization and individual RuxIn2-xO3 nanocrystals dispersion for photocatalytic CO2 reduction reaction. It results in the maximum ethanol production rate up to 31.6 μmol/g/h with over 90% selectivity. DFT simulation reveals that the C2 dimer formation primarily underwent an asymmetric *CO-*CHO coupling route via a low-energy precedence ladder of *CHO. This work provides an insightful understanding of active sites with dynamic reconstruction towards asymmetric C-C coupling for CO2RR at the atomic scale. Understanding the role of atomic sites in photocatalytic CO2 reduction remains challenging. This study provides insights into dynamic Ruδ+-O/Ru0-O pair reconstruction and explores approaches to enhancing intermediate regulation and asymmetric *CO-*CHO coupling for producing C2+ products.
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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".