Kinetics of the Absorption of CO<sub>2</sub>into Mixed Aqueous Loaded Solutions of Monoethanolamine and Methyldiethanolamine
Bibliographic record
Abstract
The kinetics of absorption of CO 2 in loaded mixed methyldiethanolamine (MDEA) and monoethanolamine (MEA) solutions was investigated in a laboratory laminar jet apparatus. The experiments were conducted over the temperature range of 298−333 K, MDEA/MEA wt ratio of 27/03, 25/05 and 23/07, total amine concentration of 30 wt %, and CO 2 loading from 0.005 to 0.15 (mol of CO 2 )/(mol of total amine). Physical properties such as density, viscosity, diffusivity, and solubility of the system were calculated from published data and/or models. Reaction mechanisms, namely, zwitterion and termolecular, were used to interpret the kinetic data. It was observed that the zwitterion mechanism in its original form could not predict the individual kinetic rate constants. Equally, the termolecular mechanism with water in the apparent reaction rate term also did not yield any reasonable results. A modified termolecular mechanism, which included the contribution of hydroxide ions, was able to predict the kinetics of a CO 2 loaded mixed alkanolamine solution satisfactorily with MDEA not participating with MEA in the kinetics. Individual reaction rate constants were predicted based on the modified termolecular mechanism.
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 | 0.000 |
| 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".