Extension of the electrolyte <scp>Trebble–Bishnoi EOS</scp> to mixed‐salt systems, and application to vapour liquid and solid (hydrate) vapour liquid equilibrium calculations
Bibliographic record
Abstract
Abstract This work examines the use of the electrolyte Trebble–Bishnoi equation of state (eTBEOS) in predicting high‐pressure phase equilibria in the presence of aqueous mixed‐salt solutions. The eTBEOS combines the Trebble–Bishnoi equation of state with a Born energy term, a mean spherical approximation term, and a cation solvation term. Shortcomings in the originally regressed set of eTBEOS parameters are identified and discussed, and a new set of equation of state parameters is subsequently regressed for 58 salts. In order to extend the eTBEOS to mixed‐salt systems, two approaches for computing the EOS parameters of the ionic species are investigated. The first approach uses the originally regressed parameter set plus parameter mixing rules, where appropriate, whereas the second approach uses the newly regressed parameters and no mixing rules. In the prediction of osmotic coefficients in mixed‐salt solutions, the maximum relative difference between the experimental and computed values was 5.70%. For the gas solubility predictions, data were available for the solubility of CO 2 , CH 4 , and N 2 in a small number of mixed electrolyte solutions; the maximum relative difference was 5.79%. Finally, CH 4 , C 2 H 6 , C 3 H 8 , and CO 2 gas hydrate formation conditions were predicted in a number of mixed‐salt solutions, with a maximum relative difference of 10.76%. Overall, it was seen that both approaches allowed for comparable accuracy in phase equilibrium calculations. However, in the case of solutions made from salt mixtures with common cations, the second approach consistently resulted in improved accuracy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".