Solubility of Carbon Dioxide in Five Promising Ionic Liquids
Bibliographic record
Abstract
According to many environmental aspects, the use of ionic liquids as potential solvents for CO2 capture and natural gas sweetening processes has gained much attention from many researchers in recent years. This research experimentally determines the solubility of CO2 in five ionic liquids: triethylsulfonium bis(trifluoromethylsulfonyl)imide ([S222][Tf2N]), diethylmethyl(2-methoxyethyl)ammonium bis(trifluoromethyl sulfonyl)imide ([deme][Tf2N]), 1-propyl-3-methylimidazolium bis(trifluoro methylsulfonyl) imide ([pmim] [Tf2N]), 1-allyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([amim][Tf2N]), and 1-butyl-4-methyl pyridinium tetrafluoroborate ([4mbp][BF4]) at (313.15, 323.15 and 333.15 K) and pressures up to 20 bar using a gravimetric microbalance. The solubility of CO2 diminished in the following sequence: [deme][Tf2N]> [pmim][Tf2N] > [amim][Tf2N] > [S222][Tf2N] > [4mbp][BF4]. The solubility of CO2 in these ionic liquids increased as temperature decreased. Four studied ionic liquids, [deme][Tf2N], [pmim][Tf2N], [amim][Tf2N], [S222][Tf2N] are deemed promising because of high CO2 solubility with a physical absorption when compared to [hmim][Tf2N]. These physical solvents have lower solubility than [bmim][Ac] which exhibited a strong chemical absorption and the reported formation of a chemical complex. Henry’s law constants for the investigated ionic liquids were derived.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".