New AMP/polyamine blends for improved CO<sub>2</sub> capture: Study of kinetic and equilibrium features
Bibliographic record
Abstract
Abstract 2‐Amino‐2‐methyl‐1‐propanol (AMP), which is the sterically hindered form of monoethanolamine (MEA), is a credible substitute to conventional CO 2 ‐capturing solvents. Its performance can be improved by blending with a highly reactive polyamine promoter. Two such aqueous blends of AMP/TETA and AMP/TEPA were chosen here (TETA = triethylenetetramine and TEPA = tetraethylenepentamine). The kinetics of CO 2 absorption in the proposed blends was investigated at 308, 313, and 318 K using the stirred cell technique. The concentrations of AMP and polyamine were varied between 2 to 3 kmol/m 3 and 0.1 to 0.5 kmol/m 3 , respectively. From the measured values of the fast pseudo‐first order constants, the second‐order rate constants for the reactions of CO 2 with TETA (14 695 m 3 /(kmol s)) and TEPA (19 250 m 3 /(kmol s)) were determined at T = 313 K. Both TETA and TEPA react faster with CO 2 than MEA. Further, the respective activation energy values were found (40 and 37 kJ/mol). Finally, the equilibrium solubility of CO 2 for both blends was measured at T = 303 K. The loading capacity was higher than that for the aqueous blends of AMP/MEA, AMP/DEA, and AMP/MDEA (here, DEA and MDEA denote diethanolamine and N‐methyldiethanolamine). The highest value of loading capacity (1.12 mol CO 2 /mol amine at 2.01 kPa equilibrium partial pressure of CO 2 ) was noted in AMP/TEPA mixtures. The new findings on our proposed blends will strengthen the AMP/polyamine application in CO 2 separation.
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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".