Controlled Postgrafting of Titanium Chelates for Improved Synthesis of Ti-SBA-15 Epoxidation Catalysts
Bibliographic record
Abstract
A new synthesis procedure that is based on the grafting of titanium alkoxide species chemically modified by acetylacetone (acac) on the surface of a P123/SBA-15 composite material is proposed to prepare Ti-SBA-15 catalysts and studied by a combination of elemental analysis, Fourier transform infrared spectroscopy (FTIR), solid-state 13 C (CP) NMR, thermogravimetric analysis (TGA), X-ray diffraction (XRD), diffuse reflectance UV−vis (DR-UV−vis), and N 2 physisorption at −196 °C. In the absence of the acac chelates, the observed formation of anatase TiO 2 onto the surface of the material demonstrates that the coordinating ligand acts as an inhibitor for the crystallization of anatase. Furthermore, FTIR and 29 Si NMR results show that the chelated titanium alkoxide precursor interacts strongly with the silanol groups, which, in turn, greatly enhances the dispersion of the titanium species in the mesoporous silica matrix. Moreover, a decrease of the temperature applied for the postgrafting and an increase of both the acac/Ti ratio and pH are shown to favor the retention of titanium on the materials surface without affecting the titanium dispersion. According to the X-ray photoelectron spectroscopy (XPS) results, a maximal titanium content of 13.8% can be well-dispersed on the surface of the mesopores without formation of an excess on the external surface of the solids. However, the results of the DR-UV−vis analyses and the catalytic epoxidation of cyclohexene reveal that the maximal concentration of titanium species in tetrahedral coordination is obtained for materials with a Ti/Si ratio of 5.6%. Even if materials with higher titanium content do not show higher conversion of cyclohexene, they do exhibit remarkably low catalytic deactivation during the recycling tests. A higher hydrothermal stability is suggested as an explanation for the lower deactivation of Ti-SBA-15 at high titanium content.
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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".