Vapour–liquid equilibrium using quantum chemical molecular dynamics simulation and radial distribution function analysis
Bibliographic record
Abstract
Abstract Instead of the classical molecular simulation widely implemented for estimating the vapour–liquid equilibrium (VLE), a quantum chemical (QC) molecular dynamics simulation was applied to the VLE estimation in three typical systems that include a deep eutectic solvent (DES) and an ionic liquid (IL). In addition, a radial distribution function (RDF) was derived from the QC simulation to examine the molecular behaviour in the liquid phase. A mean absolute error of 2.72% was obtained from the QC simulation compared to the experimental data. The RDF analysis explains the relative volatility increase of the acetic acid and water binary system with the propyl acetate solvent. This analysis indicated that the DES mixture comprising glycerol and choline chloride facilitated the separation of water and i ‐propanol. The interaction between water and ethyl sulphate pair with the help of 1‐ethyl‐3‐methylimidazolium as an IL is stronger than that between ethanol and water, which explains how the IL improves ethanol and water separation in the vapour phase.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".