Foaming Behavior in CO<sub>2</sub> Absorption Process Using Aqueous Solutions of Single and Blended Alkanolamines
Bibliographic record
Abstract
This work provides a comprehensive investigation on the effects of process parameters on foaming behavior in the carbon dioxide (CO 2 ) absorption process using aqueous alkanolamine solutions, particularly for the application of postcombustion flue gas treatment. The foaming tendency of this process was experimentally evaluated using the pneumatic method modified from ASTM standard, and reported in terms of foaminess coefficient (Σ). Results reveal ranges of solution volume and gas flow rate leading to constant values of Σ. Σ increases and eventually decreases with alkanolamine concentration and CO 2 loading. A higher solution temperature reduces Σ. Most tested degradation products and corrosion inhibitors enhance foaming tendency. Monoethanolamine (MEA), methyldiethanolamine (MDEA), and a blend of MEA + 2-amino-2-methyl-1-propanol (AMP; 2:1 mixing ratio) tend to foam, whereas diethanolamine (DEA), AMP, and blends of MEA + MDEA, DEA + MDEA and MEA + AMP (1:1 and 1:2 mixing ratio) do not. Surface tension, viscosity, and density of solutions play a major role in foaming tendency.
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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".