Vapor–Liquid Phase Equilibria and Physical Properties Measurements for Ternary Systems (Methane + Decane + Hexadecane)
Bibliographic record
Abstract
The vapor–liquid equilibrium (VLE) data for ternary systems (methane + decane + hexadecane) have been determined using a designed pressure–volume–temperature (PVT) apparatus. Three different (decane + hexadecane) binary mixtures were prepared, and the solubility and phase equilibria of three prepared mixtures with methane at ambient temperature and different pressures from (1 to 8) MPa were studied. The phase composition and saturated liquid density and viscosity were reported for each pressure. The VLE data of the ternary mixtures were correlated using Soave–Redlich–Kwong and Peng–Robinson equations of state. The equations of state models with their best-fitted parameters of the binary systems, (methane + decane and methane + hexadecane), were used to predict the VLE data of ternary systems. Both equations of state were found to be capable of describing the phase equilibria of binary pairs and ternary systems over the range of studied conditions. The Peng–Robinson equation of state gave better predictions of saturated liquid densities than those of the Soave–Redlich–Kwong equation of state.
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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 | 0.001 |
| Open science | 0.001 | 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".