Wettability Engineering of Solar Methanol Synthesis
Bibliographic record
Abstract
Engineering the wettability of surfaces with hydrophobic organics has myriad applications in heterogeneous catalysis and the large-scale chemical industry; however, the mechanisms behind may surpass the proverbial hydrophobic kinetic benefits. Herein, the well-studied In 2 O 3 methanol synthesis photocatalyst has been used as an archetype platform for a hydrophobic treatment to enhance its performance. With this strategy, the modified samples facilitated the tuning of a wide range of methanol production rates and selectivity, which were optimized at 1436 μmol g cat –1 h –1 and 61%, respectively. Based on in situ DRIFTS and temperature-programmed desorption-mass spectrometry, the surface-decorated alkylsilane coating on In 2 O 3 not only kinetically enhanced the methanol synthesis by repelling the produced polar molecules but also donated surface active H to facilitate the subsequent hydrogenation reaction. Such a wettability design strategy seems to have universal applicability, judged by its success with other CO 2 hydrogenation catalysts, including Fe 2 O 3, CeO 2, ZrO 2, and Co 3 O 4 . Based on the discovered kinetic and mechanistic benefits, the enhanced hydrogenation ability enabled by hydrophobic alkyl groups unleashes the potential of the surface organic chemistry modification strategy for other important catalytic hydrogenation reactions.
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How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".