DISQUAC predictions on thermodynamic properties of ternary and higher multicomponent mixtures. II. Results for <i>H</i><sup>E</sup> of ternary mixtures containing nonpolar components, or one polar compound, two polar compounds, or one alcohol and hydrocarbons, or CCl<sub>4</sub>
Bibliographic record
Abstract
The ability of the DISQUAC model for predicting excess enthalpies (HE) of ternary systems on the basis of binary parameters only, i.e., neglecting ternary interactions is analyzed. At this end, DISQUAC results for a set of 95 ternary systems are examined. The solutions studied are formed by only hydrocarbons (or CCl4); or by one polar compound (not alcohols) and two hydrocarbons (or CCl4); or by two polar compounds (not alcohols) and one hydrocarbon (or CCl4); or by one alcohol and two hydrocarbons (or CCl4). Most of the HEs analyzed are endothermic, and valid at 298.15 K and atmospheric pressure. The mean deviation between experimental values and DISQUAC results is 5.5% for the ternary systems and 6.5% for the constituent binaries (181 mixtures). The interaction parameters used are valid for the description of thermodynamic properties of binary systems: vaporliquid equilibria (VLE), liquidliquid (LLE), and solidliquid equilibria (SLE), HE and excess heat capacities at constant pressure (CEP), as well as HE and VLE of ternary solutions. Predictions are, in most of the cases, independent of the mixture compounds, or the number of groups present in the system. Larger deviations underline typical shortcomings of the group contributions methods (e.g., Patterson's effect; branching). Note that results for the ternaries and for the constituent binaries are of the same order. This is not the case for the Dortmund version of UNIFAC. The mean deviations obtained using this model are 10.5% and 14% for the ternary and binary mixtures, respectively. Results from other models (original UNIFAC, Flory's theory, NittaChao, UNIQUAC association model) for a number of systems are also compared to those obtained using DISQUAC.Key words: predictions, HE, ternary systems, binary parameters, geometrical methods, Flory, group contributions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".