Applications of Pore-Expanded Mesoporous Silicas. 3. Triamine Silane Grafting for Enhanced CO<sub>2</sub> Adsorption
Bibliographic record
Abstract
Conventional MCM-41 and pore-expanded MCM-41 (PE-MCM-41) silicas have been used as supports for grafting 3-[2-(2-aminoethylamino)ethylamino]propyl trimethoxysilane (TRI) and tested for CO 2 adsorption. The effects of the quantity of triamine silane added to the grafting mixture on the CO 2 adsorption capacity and apparent adsorption rate have been examined. The results showed that when both supports were grafted under the same conditions, PE-MCM-41 was grafted with slightly larger quantities of amine than MCM-41, for all controlled silane additions. Based on the adsorption performance of the materials using a dry 5% CO 2 /N 2 feed mixture, the optimal quantity of triamine silane added to the grafting mixture was determined to be ca. 3.0 cm 3 /g(SiO 2 ), for both MCM-41 and PE-MCM-41. The CO 2 adsorption capacity of TRI−PE-MCM-41 was significantly higher than that of TRI−MCM-41. Furthermore, the dynamic adsorption performance of TRI−PE-MCM-41 was far superior to TRI−MCM-41. In comparison to 13X zeolite, TRI−PE-MCM-41 exhibited higher adsorption capacities in the initial time frame of exposure, even though the 13X zeolite exhibited a higher equilibrium adsorption capacity. The result of this behavior is largely due to the rapid CO 2 −amine interaction and the open pore structure of TRI−PE-MCM-41 over that of the 13X zeolite. When these adsorbents were exposed to a humid stream of 5% CO 2 /N 2 (28% relative humidity), both grafted materials exhibited a slight increase in the adsorption capacity, whereas, 13X zeolite did not retain any significant CO 2 adsorption capacity. These results suggest that the TRI−PE-MCM-41 material may be most suitable for use in a rapid cyclic adsorption process under humid feed conditions.
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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 | 0.001 | 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".