Imidazolyl‐Functionalized Ordered Mesoporous Polymer from Nanocasting as an Effective Support for Highly Dispersed Palladium Nanoparticles in the Heck Reaction
Bibliographic record
Abstract
Abstract New imidazolyl‐functionalized ordered mesoporous cross‐linked polymers were prepared by the copolymerization of the ionic liquid 3‐benzyl‐1‐vinyl‐1H‐imidazolium bromide with divinylbenzene as the cross‐linker and azobisisobutyronitrile as the radical initiator in the presence of O‐silylated SBA‐15 as the hard template. The materials were characterized by N2 adsorption–desorption analysis, TEM, thermogravimetric analysis, elemental analysis, and FTIR spectroscopy. The material, which benefits from the use of entrapped ionic liquid in the prepared polymer matrix in combination with its ordered mesoporous structure, is an excellent environment for the stabilization of highly dispersed Pd nanoparticles to result in a recyclable catalyst system with a significant activity in the Heck coupling reaction of aryl halides. The presence of well‐distributed imidazolium functionalities in the polymeric framework might be responsible for the relatively uniform and nearly atomic scale distribution of Pd nanoparticles throughout the mesoporous structure and the prevention of Pd agglomeration during the reaction, which results in high durability, high stability, and good recycling characteristics of the catalyst. Although our catalyst system operates in a homogeneous pathway, it is also very stable and recyclable.
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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".