Optimizing Silica Synthesis for the Preparation of Mesoporous Ti-SBA-15 Epoxidation Catalysts
Bibliographic record
Abstract
The influence of the synthesis conditions of SBA-15 silica support in the development of Ti-SBA-15 epoxidation catalysts has been studied in detail. In this study, efficient and stable Ti-SBA-15 epoxidation catalysts were prepared using a recently developed postgrafting method based on the insertion of a chelated titanium alkoxide precursor inside the SBA-15 silica mesophase. First, the nature of the SBA-15 supports was analyzed as a function of different synthesis parameters, such as hydrothermal aging temperature and calcination temperature, by solid-state NMR spectroscopy, thermal analysis, and nitrogen physisorption at −196 °C. Subsequently, titanium-substituted SBA-15 materials were characterized by DR UV−vis spectroscopy, elemental analysis, and nitrogen physisorption. As a catalytic test reaction, the activity, selectivity, and catalyst regenerability were studied in the epoxidation of cyclohexene. Our findings show that the density of silanol groups on the support greatly influences the retention and coordination number of the grafted titanium species. This characteristic of the mesoporous silica supports also has an influence on the catalytic activity of the resulting titanosilicate materials. The conversion of cyclohexene obtained with Ti-SBA-15 catalysts synthesized using noncalcined mesoporous silica was found to increase with the hydrothermal aging temperature of the support. Furthermore, the results showed that higher conversions of cyclohexene were obtained with catalysts prepared using SBA-15 calcined at 550 °C prior to the Ti grafting step, although lower dispersion of the titanium species was usually observed for these materials. A higher accessibility of the substrates to the active sites on the surface of these materials can explain these results. However, a dramatic deactivation of the catalysts was observed upon recycling of these active materials. In contrast, the grafted catalysts prepared using uncalcined mesoporous silica supports showed a substantially lower catalytic deactivation upon different reaction cycles as compared to those grafted after calcination.
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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) | 0.001 | 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".