Reaction Kinetics of CO<sub>2</sub> in Aqueous Ethylenediamine, Ethyl Ethanolamine, and Diethyl Monoethanolamine Solutions in the Temperature Range of 298−313 K, Using the Stopped-Flow Technique
Bibliographic record
Abstract
The observed pseudo-first-order rate constants ( k 0 ) for the reactions between CO 2 and ethylenediamine (EDA), ethyl ethanolamine (EEA), and diethyl monoethanolamine (DEMEA) have been studied using the stopped-flow technique in an aqueous solution at 298, 303, 308, and 313 K. The amine concentrations ranged from 26.2 mol/m 3 to 67.6 mol/m 3 for EDA, 28.2 mol/m 3 to 81.9 mol/m 3 for EEA, and 196.5 mol/m 3 to 997.4 mol/m 3 for DEMEA. The zwitterion mechanism was used to correlate the experimentally obtained rate constants. Both the zwitterion formation step and the proton removal step had a significant role for the primary and secondary amines (EDA and EEA). The reaction rate of CO 2 in an aqueous EDA solution was observed to be much faster than that in aqueous MEA solution. The rate in aqueous EEA was much faster than in aqueous DEA, under the conditions studied. Finally, the reaction rate constant of CO 2 in an aqueous tertiary amine (DEMEA) solution was observed to be much faster than that in methyl diethanolamine (MDEA). Only the zwitterion formation step had a significant role in the overall reaction. The base catalysis of the CO 2 hydration mechanism could explain the reaction between CO 2 and the tertiary amine. Therefore, the three selected amines are considered to be of interest to the gas sweetening industry.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".