Hydrocarbons – water phase equilibria using the CPA equation of state with a group contribution method
Bibliographic record
Abstract
Abstract It is proposed in this paper to extend the original group contribution method PPR78 to systems containing water, by combining it to the Cubic–Plus–Association (CPA) equation of state (EoS). Applying simple geometric combination rules, the binary interaction parameter k ij (T) can be calculated from interaction parameters between hydrocarbon groups and water. This model, called the GC–PR–CPA is applied to predict hydrocarbons – water mutual solubilities over a wide temperature and pressure range, depending on available literature data. Group interaction parameters, here CH 4 , C 2 H 6 , CH 3 , CH 2 , CH, C, CH aro , CH 2,cyclic , CH cyclic /C cyclic , C 2 H 4 , CH 2,alkene /CH alkene with H 2 O have been defined with solubility data. Predictions of the developed model have been validated against independent solubility data as well as water content in hydrocarbon rich phase. Predictions of the new model are in good agreement for light and medium hydrocarbons; however, some deviations are observed for heavier hydrocarbons.
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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 | 0.001 | 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".