Lewis acidity quantification and catalytic activity of Ti, Zr and Al-supported mesoporous silica
Bibliographic record
Abstract
Water-tolerant supported Lewis acids are actively sought after, in particular to address the challenging direct amidation reaction. To this aim, a versatile and easy synthesis of large pore silica materials with supported Ti-, Al-, Zr-Lewis acids, using acetyl acetonate as a metal-stabilizing agent, was accomplished. The formation of bulk metal oxides was not observed, even at high concentrations of metal species. The Lewis acidity was demonstrated using quantitative and qualitative titration techniques using a series of Hammett indicators, such as butter yellow, phenylazodiphenylphosphine and dicinnamalacetone. The optimal concentration of metals corresponding to the highest Lewis acidity of solids was found to be 4% for Al-SBA-15, 12-15% for Ti-SBA-15 and 7% for Zr-SBA-15 materials. The water-tolerance of the supported metal centers was explored by a pyridine adsorption-FTIR study before and after water addition. The metalated materials were used as water-tolerant heterogeneous catalysts for the amidation of electron-poor and bulky amines, such as substituted anilines and morpholine, obtaining 59-99% yield of the corresponding amides.
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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".