Visible-Light-Driven Methanol-To-Ethanol Conversion via Carbene Pathway by Frustrated Lewis Pairs
Bibliographic record
Abstract
Carbenes are critical intermediates in organic chemistry, recognized for their exceptional reactivity and versatility. However, conventional methods for carbene generation are often associated with safety risks and hazardous procedures. This study presents a Ga-ZnO 1– x nanosheets photocatalyst with a (100) preferred orientation, featuring abundant refined frustrated Lewis pair (FLP) sites, excellent light absorption, and efficient charge transport properties. Under visible light irradiation, this catalyst activates methanol to generate a methyl carbene (methylene) intermediate, which subsequently reacts with another methanol molecule to produce ethanol. In situ experiments and theoretical calculations reveal that FLP sites, composed of oxygen vacancies and Ga, respectively activate C–H and C–O bonds while efficiently capturing photogenerated electrons and holes, making the most significant contribution to the formation of carbene intermediates. This research not only offers an eco-friendly route for methanol-to-ethanol conversion but also establishes a safer and more efficient method for methyl carbene production under mild conditions.
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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".