Amine-Functionalized Mesoporous Silica as a Support for on-Demand Release of Copper in the A<sup>3</sup>-Coupling Reaction: Ultralow Concentration Catalysis and Confinement Effect
Bibliographic record
Abstract
The study of catalysts activity at ultralow concentration is of prime importance for the development of more sustainable catalytic processes. In this work, we designed a mesoporous MCM-41 silica with covalent functionalization with amine groups at different levels of coverage. This material was used as a support to immobilize small quantities of Cu(I) species to be used as a catalyst in the A 3 -coupling reaction. The support design allowed controlled release of the catalytically active species as well as its scavenging after reaction. This system achieved excellent catalytic performance, leading to 95% yield of the desired propargylamine within 2 h of reaction at 100 °C under microwave conditions, using only 0.02 mol % of catalyst, the lowest catalyst amount ever reported for this reaction and high TON (4750) and TOF (2375 h –1 ). An interesting effect was noticed, where the catalyst on the support yielded improved reaction rates as compared to unsupported catalysts in solution under the same concentration conditions. We discuss the possibility of a confinement of metal species inside the mesoporous structure of the support, which made the immobilized system more effective than its homogeneous counterpart. The present study pushes the limits of A 3 -coupling reaction conditions and the potential of supported metal catalysis.
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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".