Application of Peng-Robinson Equation of State for Calculating Solid-Vapor and Solid-Liquid Equilibrium of CH4-CO2 System
Bibliographic record
Abstract
In this study, the performances of Peng-Robinson Equation of State combined with the classical mixing ruleswere evaluated to calculate solid-vapor equilibrium (SVE) and solid-liquid equilibrium (SLE) of CH4-CO2system. The evaluation was performed by comparing the calculated values with the literature data. In thecalculation of SVE, the new binary interaction parameter values (kij) of CH4-CO2 mixtures were proposed in thiswork based on the experimental data. The proposed kij obtained in this work might increase the accuracy ofPeng-Robinson Equation of State by reducing average absolute deviation in the temperatures between calculatedvalues and literature data from (2.18% to 0.26%), (0.88% to 0.70%) and (0.61% to 0.44%) at CO2 compositionof 1%, 1.91% and 2.93%, respectively. Significant improvement was found at CO2 composition of 1%. In thecalculation of SLE, new parameters were not proposed since the calculation using the existing (literature) kijgives good results with an average absolute deviation of 0.5%.
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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 | 0.001 | 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".