Physicochemical Characteristics for CO<sub>2</sub>-Loaded Aqueous Bis(3-aminopropyl)amine and Its Mixture with 2-Amino-2-methyl-1-propanol
Bibliographic record
Abstract
Removal of CO 2 from industrial exhaust gas is vital and is commonly achieved by using chemical absorption with newly formulated solvents. The density and viscosity of carbonated solutions are critical physicochemical properties for selecting an efficient solvent in the CO 2 absorption processes. In this work, aqueous bis(3-aminopropyl)amine (APA) and its mixture with 2-amino-2-methyl-1-propanol (AMP) are considered to be promising absorbents for the CO 2 capture process. New experimental density and viscosity data for CO 2 -loaded APA and APA + AMP mixtures were determined over a temperature range of 303.25–328.25 K and different CO 2 concentrations pertaining to the gas absorption condition. The density and viscosity of the CO 2 -loaded APA and APA-AMP solvent systems were correlated using thermodynamics models, with parameters determined for different aqueous carbonated solvent compositions across the studied temperature range. The modeling results show that the percentage average absolute deviations (% AADs) between the experimental and model results of density were 0.03 for the ternary system (APA + H 2 O + CO 2 ) and 0.13 for the quaternary system (APA + AMP + H 2 O + CO 2 ). The % AADs between experimental and model viscosity data are 0.88 and 2.97, respectively. The obtained results provide valuable insights into the development of amine-based solvents for efficient CO 2 capture applications.
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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".