Hydrophobic Polyhedral Oligomeric Silsesquioxane Support Enhanced Methanol Production from CO<sub>2</sub> Hydrogenation
Bibliographic record
Abstract
The abundance of CO 2 from the cement industry, power generation, petroleum production, and combustion of biomass makes it a readily available feedstock to produce chemicals and materials, although it has yet to achieve optimal development. Even though syngas (CO + H 2 ) hydrogenation to methanol is an established industrial process, when the same catalytic system based on Cu/ZnO/Al 2 O 3 is employed with CO 2, the water formed as a byproduct reduces the activity, stability, and selectivity of the process. Here, we explored the potential of phenyl polyhedral oligomeric silsesquioxane (POSS) as a hydrophobic support of Cu/ZnO for direct CO 2 hydrogenation to methanol. Mild calcination of the copper–zinc-impregnated POSS material affords the formation of CuZn-POSS nanoparticles with Cu and ZnO homogeneously dispersed with an average particle size of 7 and 15 nm supported on O-POSS and D-POSS, respectively. The composite supported on D-POSS was able to reach a 3.8% yield of methanol with a 4.4% of CO 2 conversion and with selectivity as high as 87.5% within 18 h. The structural investigation of the catalytic system reveals that CuO/ZnO are electron withdrawers in the presence of the siloxane cage of POSS. The catalytic system metal-POSS is stable and recyclable under H 2 reduction and CO 2 /H 2 conditions. We tested the use of microbatch reactors in heterogeneous reactions as a rapid and effective tool for catalyst screening. The increased number of phenyls in the structure of POSS results in an increased hydrophobic character that plays a decisive role in the methanol formation after comparison with CuO/ZnO supported on reduced graphene oxide with 0% selectivity to methanol under the study conditions. The materials were characterized using scanning electron microscopy, transmission electron microscopy, attenuated total reflection Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, powder X-ray diffraction, Fourier transform infrared analysis, Brunauer–Emmett–Teller specific surface area analysis, contact angle, and thermogravimetry. The gaseous products were characterized by gas chromatography coupled with thermal conductivity detectors and flame ionization detectors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.012 |
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; both teacher heads agree on what is shown here.
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".