Effect of the Presence of MEA on the CO<sub>2</sub> Capture Ability of Superbase Ionic Liquids
Bibliographic record
Abstract
Abstract The miscibility of monoethanolamine (MEA) in five superbase ionic liquids (ILs), namely the trihexyl-tetradecylphosphonium benzotriazolide ([P66614][Bentriz]), trihexyl-tetradecylphosphonium benzimidazolide ([P66614][Benzim]), trihexyl-tetradecylphosphonium 1,2,3-triazolide ([P66614][123Triz]), trihexyl-tetradecylphosphonium 1,2,4-triazolide ([P66614][124Triz]), and trihexyl-tetradecylphosphonium imidazolide ([P66614][Im]) was determined at 295.15 K using 1H NMR spectroscopy. The solubility of carbon dioxide (CO2) in equimolar (IL + MEA) mixtures was then studied experimentally using a gravimetric technique at 295.15 K and 0.1 MPa. The effect of MEA on the CO2 capture ability of these ILs was investigated together with the viscosity of these systems in the presence or absence of CO2 to evaluate their practical application in CO2 capture processes. The effect of the presence of MEA on the rate of CO2 uptake was also studied. The study showed that the MEA can enhance CO2 absorption over the ideal values in the case of [P66614][123Triz] and [P66614][Bentriz] while in the other systems the mixtures behave ideally. A comparison of the effect of MEA addition with the addition of water to these superbase ILs showed that similar trends were observed in each case for the individual ILs studied.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".