New Insights into the Interactions of CO<sub>2</sub> with Amine-Functionalized Silica
Bibliographic record
Abstract
The CO 2 −amine chemistry in gas−solid processes was investigated under both humid and dry conditions using aminopropyl-grafted pore-expanded MCM-41 silica (MONO-PE-MCM-41). To draw accurate conclusions, a set of conditions had to be met including (i) the use of an adsorbent with open pore structure and readily accessible adsorption sites, e.g. MONO-PE-MCM-41 with a mean pore size of 7.2 nm; (ii) the CO 2 concentration in the feed should be high enough to achieve saturation via chemisorption, but low enough to avoid any additional physisorption, e.g., 5% CO 2 in N 2; (iii) the use of a reliable method for the accurate measurement of CO 2 /N ratio. Under such conditions, the obtained CO 2 /N ratios were reminiscent of those obtained in the CO 2 scrubbing process using ethanolamine solutions. Under dry conditions, the CO 2 /N ratio was close to 0.5, consistent with the formation of carbamate. Streams with relative humidity (RH) of 27, 61, and 74% were studied as well. As RH in the feed increased, CO 2 /N ratio increased from 0.57 to 0.88, in line with the gradual formation of bicarbonate. As for the determination of CO 2 /N ratio under dry conditions, both thermogravimetry (TG) and mass spectrometry (MS) were suitable, whereas in the presence of moisture, TG was found to drastically underestimate the CO 2 uptake. The seemingly disparate CO 2 /N ratios reported in the literature for various propylamine-bearing adsorbents were rationalized on the basis of the adsorbent pore structure and/or the experimental conditions used.
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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) | 0.001 | 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".