The comparative modeling of solubility of carbon dioxide in amine solutions using SAFT-HR and PC-SAFT equation of state
Bibliographic record
Abstract
In this paper, we applied PC-SAFT and SAFT-HR equations of state so as to reproduce the solubility of carbon dioxide in aqueous diethanolamine solution. By using these equations, we have been able to model the solubility of carbon dioxide in aqueous amine solution in more than 350 experimental data points with wide range of amine molar concentration (0.01–0.12), temperature (300 K –478 K), carbon dioxide partial pressure (0.0001 KPa –5473 KPa), and carbon dioxide loading (0.04 –1.1). Ternary systems including water, carbon dioxide and diethanolamine have also been modeled by PC-SAFT and SAFT-HR equations of state based on bubble pressure algorithm. Binary interaction parameters are set to zero to show the genuine capability of equations of state in reproducing such experimental data. Provided modeling results have been obtained from MATLAB R2019b software for PC-SAFT equation of state are less deviated with experimental data. Overall average relative deviation of SAFT-HR and PC-SAFT are 45.452% and 4.374% respectively which show that PC-SAFT is a robust equation of state in predicting the solubility data of carbon dioxide in aqueous alkanolamine solutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".