Advanced association theory for monoethylene glycol: thermodynamic perturbation theory, Monte Carlo simulation, and equation of state parametrization
Bibliographic record
Abstract
Thermodynamic perturbation theory (TPT) is a breakthrough in developing an equation of state for systems containing hydrogen bonding. In this work, we derive the association contribution to Helmholtz's free energy for spherical particles composed of four patchy sites and verified it by performing Monte Carlo (MC) simulations. The theory suggests that the site placement significantly impacts the system's phase behavior at constant temperature and density. We apply our theory to correlate and predict the experimental phase behavior data of pure monoethylene glycol (MEG) and its binary mixtures with non-associating molecules (including methane, ethane, propane, and hydrogen) and compare the theory's performance with the case where the association contribution to the system's pressure is based on first-order TPT (TPT1). Our theory outperforms TPT1 in terms of error and predictive capabilities for the physical properties of pure MEG. In the binary mixture application, TPT1 presents a better predictive ability for the mole fraction of the non-associating molecule in the glycol-rich liquid than our theory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".