Substantiating the Influence of Pore Surface Functionalities on the Stability of Grubbs Catalyst in Mesoporous SBA‐15 Silica
Bibliographic record
Abstract
The influence of pore surface functionalities in mesoporous SBA-15 silica on the stability of a model olefin metathesis catalyst, namely Grubbs I, is substantiated. In particular, it is demonstrated that the nature of the interaction between the ruthenium complex and the surface is strongly depending on the presence of surface silanols. For this study, differently functionalized mesoporous SBA-15 silica materials were synthesized according to standard procedures and, subsequently, the Grubbs I catalyst was incorporated into these different host materials. All of the materials were thoroughly characterized by elemental analyses, nitrogen physisorption at -196 °C, thermogravimetric analyses, solid-state NMR spectroscopy, and infrared spectroscopy (ATR-IR). By such in-depth characterization of the materials, it became possible to achieve models for the surface/catalyst interactions as a function of surface functionalities in SBA-15; for example, in the case of purely siliceous silanol-rich SBA-15, octenyl-silane modified SBA-15, and silylated equivalents. It was evidenced that large portions of the chemisorbed species that are detected spectroscopically arise from interactions between the tricyclohexylphosphine and the surface silanols. A catalytic study using diethyldiallylmalonate in presence of the various functionalized silicas shows that the presence of surface silanols significantly decreases the longevity of the ring-closing metathesis catalyst, whereas the passivation of the surface by trimethylsilyl groups slows down the catalysis rate, but does not affect significantly the lifetime of the catalyst. This contribution thus provides new insights into the functionalization of SBA-15 materials and the role of surface interactions for the grafting of organometallic complexes.
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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".