Palladium Nanoparticles Supported in the Nanospaces of Imidazolium-Based Bifunctional PMOs: The Role of Plugs in Selectivity Changeover in Aerobic Oxidation of Alcohols
Bibliographic record
Abstract
Novel heterogeneous catalyst systems comprised of palladium nanoparticles immobilized into the nanospaces of imidazolium-based bifunctional plugged and unplugged periodic mesoporous organosilicas (BFPMO) have been described for the selective aerobic oxidation of alcohols in water. BFPMOs were characterized by N 2 adsorption–desorption analysis, transmission electron microscopy (TEM), powder X-ray diffraction (PXRD), thermal gravimetric analysis (TGA), 29 Si and 13 C cross-polarization magic angle spinning (CP MAS) NMR spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy (DRIFT), elemental analysis, scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The catalytic activity of all plugged and unplugged catalysts was investigated in the aerobic oxidation of benzylic alcohols by emphasizing the effect of different physiochemical properties as well as the plugs on the reaction selectivity. While unplugged catalysts exhibited much better activity for the selective oxidation of benzyl alcohol to benzaldehyde, the selectivity pattern shifts to the benzoic acid in high yield and selectivity in the presence of plugged catalyst under the exact same reaction conditions. The studies showed for the first time that varying the hydrophobic–hydrophilic balance with concomitant control of plugs in the interior of the mesochannels of the described catalyst enabled tuning of both the catalyst performance and the reaction selectivity, possibly through a cooperative mechanism. A possible model has been proposed to explain this unprecedented observation.
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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) | 0.000 | 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 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".