Peng–Robinson or Redlich–Kwong? Twu or Soave α-Function? Which Combination of Cubic Equation of State (CEoS) and α-Function Produces More Accurate and Consistent Results for Pure Components
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide This study tested the accuracy and thermodynamic consistency of four CEoS/α-function models. The objective was to find the most suitable CEoS/α-function combo for producing accurate and consistent physical and derivative properties for nonpolar, polar and hydrogen bonding components at subcritical conditions. The models tested were PR-Twu, PR-Soave, RK-Twu, and RK-Soave. The first term in the model’s name refers to the CEoS used: Peng–Robinson (PR) or Redlich–Kwong (RK). The second term indicates the α-function used, i.e., Twu’s or Soave’s. The models were tested on a data set containing saturation pressure, enthalpy of vaporization and saturated liquid heat capacity of 147 pure components classified as polar, nonpolar, and hydrogen bonding. The three Twu α-function parameters were fitted to data and constrained to produce thermodynamic consistent values across the phase diagram; and, the Soave α-function parameter was predicted from a well-known correlation. The thermodynamic consistency of the models was assessed by calculating the Waring number and the saturated liquid speed of sound of 147 and 79 pure components, respectively. The results showed that PR-Twu and RK-Twu produced more accurate pure component properties compared to those from PR-Soave and RK-Soave. However, there was not a significant difference between the performance of PR-Twu and RK-Twu for calculating pure component properties. The same result was obtained when comparing PR-Soave and RK-Soave. Interestingly, the consistency analysis showed that only PR-Twu and PR-Soave produced consistent Waring number trends for components with acentric factors below 0.7. It was also observed that the saturated liquid speed of sound calculated from all four models tested was not accurate as the models cannot produce precise −(∂ P ∂ v) T and liquid volumes. Besides, using volume translation is detrimental to the accuracy of the calculated saturated liquid speed of sound. The most accurate and consistent model was PR-Twu; however, caution should be exercised when modeling the saturated liquid heat capacity of hydrogen bonding components.
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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".