The analysis of solubility, absorption kinetics of CO<sub>2</sub> absorption into aqueous 1‐diethylamino‐2‐propanol solution
Bibliographic record
Abstract
In this present work, the CO 2 absorption performance of aqueous 1‐diethylamino‐2‐propanol (1DEA2P) solution was studied with respect to CO 2 equilibrium solubility, absorption kinetics, and absorption heat. The equilibrium solubility of CO 2 in 2M 1DEA2P solution was measured over the temperature range from 298 to 333 K and CO 2 partial pressure range from 8 to101 kPa. The absorption kinetics data were developed and analyzed using the base‐catalyzed hydration mechanism and artificial neural network models (radial basis function neural network [RBFNN] and back‐propagation neural network [BPNN] models) with an acceptable absolute average deviation of 10% for base‐catalyzed hydration mechanism, 2.6% for RBFNN model and 1.77% for BPNN model, respectively. The CO 2 absorption heat of 1DEA2P was estimated to be −43.6 kJ/mol. In addition, the ions (1DEA2P, 1DEA2PH + , , CO 3 2− ) speciation plots of the 1DEA2P‐CO 2 ‐H 2 O system were developed to further understand the reaction process of 1DEA2P with CO 2 . Based on a comparison with conventional amines (e.g., MEA, DEA, MDEA) and alternative amines (i.e., 1DMA2P and 4‐(diethylamino)−2‐butanol [DEAB]), 1DEA2P exhibited good performance with respect to CO 2 equilibrium solubility, reaction kinetics, and CO 2 absorption heat. Meanwhile, the overall evaluation of 1DEA2P for application in CCS in terms of absorption and desorption is presented, giving helpful information for the screening of these novel amines. © 2017 American Institute of Chemical Engineers AIChE J , 63: 2694–2704, 2017
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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".