Applications of Pore-Expanded Mesoporous Silica. 5. Triamine Grafted Material with Exceptional CO<sub>2</sub> Dynamic and Equilibrium Adsorption Performance
Bibliographic record
Abstract
Application of pore-expanded MCM-41 (PE-MCM-41) mesoporous silica coated with 3-[2-(2-aminoethylamino)ethylamino]propyltrimethoxysilane (TRI) has been extensively examined for the adsorption of CO 2 from N 2 . A systematic study of the amine loading as a function of the relative amounts of TRI and water used during the grafting procedure and the temperature of the grafting reaction was carried out. Extremely high levels of active amine content were achieved using prehydrated silica surfaces at grafting temperatures below reflux in order to facilitate thermally controlled water-aided surface polymerization of the aminosilanes. The CO 2 adsorption capacities and rates were determined for all materials as a function of the amount of TRI and water per gram of support added to the grafting mixture. The optimal TRI grafted PE-MCM-41 adsorbent exhibited a 2.65 mmol/g adsorption capacity at 25 °C and 1.0 atm for a dry 5% CO 2 in N 2 feed mixture, which exceeded all literature reported values, for both meso- and microporous materials under the conditions used in this study. Further, the apparent adsorption and desorption rates with the amine functionalized materials were exceedingly high. When considering the grafted amine quantity, the adsorption capacity and rate were found to be mutually dependent on each other, exhibiting an apparent optimal combination. In comparison to zeolite 13X, the optimally loaded TRI-PE-MCM-41 was far superior in terms of dynamic adsorption and desorption performance. These results were further enhanced when the adsorbents were challenged with a humid stream of 5% CO 2 /N 2 . The TRI-PE-MCM-41 exhibited a 10% increase in CO 2 adsorption capacity, whereas the 13X zeolite did not retain any significant CO 2 adsorption capacity.
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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".