Effect of Water Vapor on CO<sub>2</sub> Sorption–Desorption Behaviors of Supported Amino Acid Ionic Liquid Sorbents on Porous Microspheres
Bibliographic record
Abstract
Immobilizing amino acid ionic liquids (AAILs) into a porous support is a promising way to fabricate robust solid sorbents with high capacities for CO 2 capture. One of important factors to be evaluated toward the practical use is the impact of water vapor in inlet gases on the CO 2 capture performance as real flue gases contain some fraction of water vapor. In this study, CO 2 sorption–desorption experiments of supported 1-ethyl-3-methylimidazolium amino acid ([EMIM][AA]) IL sorbents on porous microspheres were conducted under dry and humidified CO 2 inlet conditions using a TGA-MS analysis system, and their outcomes were compared with those of supported amino acids (AA) sorbents. The presence of water vapor changed the CO 2 sorption behaviors depending on the sorbent types. In humidified CO 2 inlet, the CO 2 capture capacities of supported [EMIM][glycine] and [EMIM][lysine] decreased as the adsorbed water hindered their reaction with CO 2, whereas the CO 2 capture of those with supported lysine and arginine increased, since water content exerted a positive impact on the CO 2 capture behavior.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".