Determination of Mutual Solubility between CO<sub>2</sub> and Water by Using the Peng–Robinson Equation of State with Modified Alpha Function and Binary Interaction Parameter
Bibliographic record
Abstract
Techniques have been developed to determine mutual solubility between CO 2 and water by using the Peng–Robinson equation of state (PR EOS) with a modified alpha function and a new binary interaction parameter (BIP) correlation in the presence and absence of hydrocarbons. More specifically, the alpha function for the water compound is modified by improving its prediction for water vapor pressure in the full temperature range of 273.16 to 647.10 K with an overall absolute average relative deviation (AARD) of 0.07%. Also, the polynomial temperature-dependent BIP correlation for the CO 2 –water pair in the aqueous phase is proposed by matching CO 2 solubility in water at temperatures from 273.15 to 448.15 K and pressures up to 100 MPa. It is found that the newly modified alpha function together with the proposed BIP correlation provides more accurate prediction of the CO 2 solubility in water with an overall AARD of 6.12%, compared with 8.67% from the previous exponential BIP correlation. As for the nonaqueous phase of the binary CO 2 –water system, it is found that a constant BIP for the CO 2 –water pair generally results in a good agreement between the reported and predicted compositions of the CO 2 -rich phase. Furthermore, the accurate solubility prediction of either CH 4 or CO 2 in the water-rich phase of the ternary CH 4 –CO 2 –water systems has been achieved with an overall AARD of 6.15% at a temperature of 344.15 K and pressures of 10, 20, 50, and 75 MPa, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".