Comparison between Experimental and Theoretical Estimations of the Thermal Expansion, Concentration Expansion Coefficients, and Viscosity for Binary Mixtures under Pressures up to 20 MPa
Bibliographic record
Abstract
In this work, we have measured the densities of binary mixtures of n -dodecane, 1-phenyl-2-methylpropane, and 1,2,3,4-tetrahydronaphthalene for pressures varying from (0.1 to 20) MPa at an average temperature of 25 °C. By a derivative method, we have determined the thermal expansion and concentration expansion coefficients for binary mixtures of equal mass fraction. In addition, viscosities have been measured and compared with theoretical estimates. To accurately predict the thermal expansion and concentration expansion coefficients, the densities of the binary mixtures were calculated using PC-SAFT, Peng-Robinson, and volume translated Peng-Robinson equations of state. The comparison with measured densities showed that PC-SAFT has a better agreement with experimental data than the other equations of state. From calculated densities we evaluated the thermal expansion and concentration expansion variation coefficients. We have found that PC-SAFT gives a suitable prediction for the two derivative properties unlike the two other equations of state. The combination of the model of Lohrenz-Bray-Clark for the viscosity of liquid mixtures and the densities calculated with the three equations of state gave a poor prediction of the viscosities of the binary mixtures.
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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 | 0.000 |
| 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".