On the <scp> CO <sub>2</sub> </scp> absorption kinetics, loading capacity, and catalytic desorption of aqueous solutions of <i>N</i> ‐methyl‐ <i>D</i> ‐glucamine
Bibliographic record
Abstract
Abstract CO 2 separation with harmful chemicals will damage the environment. It is essential to explore greener solvents that are producible from renewable resources such as biomass. The suitability of N ‐methyl‐ D ‐glucamine (MG), also known as meglumine, for capturing CO 2 , was explored in this work. This nontoxic amino sugar, which is derived from sorbitol, represents a renewable bio‐solvent. It was found that MG is especially reactive with CO 2 . Trials were performed in a stirred cell reactor with a flat gas–liquid interface between 303 and 313 K. The values of the pseudo‐first‐order reaction rate constant, reaction orders, and activation energy were found. The loading capacity ( α ) of 0.5 M MG solution was measured at T = 308 K. For a typical value of α = 0.524 mol CO 2 /mol MG, the corresponding equilibrium partial pressure of CO 2 was 22 kPa. Finally, it was found that the catalyst Al 2 O 3 aided in the desorption of CO 2 ‐loaded MG solutions. Desorption efficiency using Al 2 O 3 was higher (74%) than that achieved without this catalyst (45%). It is thus clear that MG represents a potential solvent for improved CO 2 separation from gases.
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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".