Water Solubility in Supercritical Methane, Nitrogen, and Carbon Dioxide: Measurement and Modeling from 422 to 483 K and Pressures from 3.6 to 134 MPa
Bibliographic record
Abstract
A series of experiments to measure the water solubility in supercritical nitrogen and carbon dioxide have been conducted at experimental conditions up to 483 K and 134 MPa. The accuracy of the experimental procedure is verified by comparing the water content data of methane in the literature and our experimental data for the methane−water system. In addition, a fugacity−fugacity approach including the cubic-plus-association equation of state (CPA EoS) and a fugacity−activity approach based on the Peng−Robinson EoS and the Henry’s law model are incorporated to predict the water content data of methane, nitrogen, and carbon dioxide. A comparison between our experimental data, literature data, and the results of the fugacity−activity approach shows the reliability of the PR-Henry’s law model for the phase behavior studies of the nitrogen−water system over a wide range of pressure and temperature conditions. However, the CPA equation is not capable of reproducing the high pressure vapor and liquid phase compositions of the water−nitrogen system. The concept of cross-association satisfactorily improves the performance of the CPA equation of state in predicting the water content data of supercritical methane. On the basis of the literature and new measured data in this study, it has been found that the CPA equation better represents the phase behavior of the water−carbon dioxide system if carbon dioxide is considered as a self- and cross-associating molecule.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".