Sun-simulated-driven production of high-purity methanol from carbon dioxide
Bibliographic record
Abstract
CO2 conversion to CH3OH under mild conditions is of particular interest yet rather challenging. Both electro- and thermo-catalytic CO2 reduction to CH3OH can only produce CH3OH in low concentration (typically mixed with water), requiring energy-intensive purification processes. Here we design a sun-simulated-driven tandem catalytic system comprising CO2 electroreduction to syngas, and further photothermal conversion into high-purity CH3OH (volume fraction > 97%). We construct a self-supporting electrocatalyst featuring dual active sites of Ni single atoms and encapsulated Co nanoparticles, which could produce syngas with a constant H2:CO ratio of ~2 via solar-powered CO2 electroreduction. The generated syngas is subsequently fed into the photothermal module, which could produce high-purity CH3OH under 1 sun-light irradiation, with a rate of 0.238 gCH3OH gcat–1 h–1. This work demonstrates a feasible and sustainable route for directly converting CO2 into high-purity CH3OH. CO2 conversion to CH3OH under mild conditions is of particular interest yet rather challenging. Here, the authors report a sun-simulated-driven tandem catalytic system comprising CO2 electroreduction to syngas, and further photothermal conversion into high-purity CH3OH (volume fraction <97%).
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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".