Novel Route to Periodic Mesoporous Aminosilicas, PMAs: Ammonolysis of Periodic Mesoporous Organosilicas
Bibliographic record
Abstract
A new route to periodic mesoporous aminosilicas (PMAs) that contain amine functional groups in the framework of a mesoporous network is reported. The materials are prepared via thermal ammonolysis of periodic mesoporous organosilicas (PMOs) under a flow of ammonia gas. PMOs integrate similar or even higher quantities of nitrogen-containing groups upon ammonolysis than similarly treated ordered mesoporous silicas (MCM-41). The quantity of amine groups introduced into the materials was found to depend strongly on the ammonolysis temperature. The largest loading of amine groups was obtained when a well-ordered cubic methylene PMO material without prior vacuum-drying was thermolyzed in ammonia. The ordered mesoporosity of PMOs was preserved during the ammonolysis with only a slight decrease in the mesopore size and the degree of mesostructural ordering. The extent of substitution of framework oxygen by amine and nitride groups was established by solid-state (29)Si CP-MAS, (29)Si MAS, (15)N MAS, and (13)C CP-MAS NMR spectroscopies, elemental analysis, and X-ray photoelectron spectroscopy. In some cases, methylene and methyl functional groups were also present in the PMAs along with amine functional groups, as inferred from elemental analysis and gas adsorption, particularly in cases where PMOs were subjected to ammonolysis at 400 and 550 degrees C for several hours. This resulted in new multifunctional mesoporous organoaminosilica nanomaterials with properties that could be tuned by systematically varying the relative amounts of hydrophilic amine and hydrophobic hydrocarbon pendent and framework groups. The stability upon storage was found to be much higher for PMAs obtained from PMOs than for those obtained from MCM-41 silicas under the same conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".