Thermodynamics of binary mixtures containing a very strongly polar compound — Part 3: DISQUAC characterization of NMP + organic solvent mixtures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Binary mixtures of 1-methyl pyrrolidin-2-one (NMP) with alkanes, benzene, toluene, 1-alkanol, or 1-alkyne have been investigated in the framework of the DISQUAC model. The reported interaction parameters change regularly with the molecular structure of the mixture components. The model consistently describes a set of thermodynamic properties, including liquid–liquid equilibria, vapor–liquid equilibria, solid–liquid equilibria, and molar excess enthalpies. A brief comparison of the DISQUAC results and those obtained from the UNIFAC and ERAS models is presented. The experimental excess enthalpies are better represented by DISQUAC than by UNIFAC because this quantity strongly depends on molecular structure. For NMP + alkane mixtures, the liquid–liquid equilibria data are also better represented by DISQUAC, while UNIFAC more accurately describes the vapor–liquid equilibria measurements at temperatures close to the critical point. This result suggests that a mean field theory is not able to represent simultaneously, with the same set of interaction parameters, liquid–liquid and vapor–liquid equilibria at the mentioned temperatures. ERAS fails when treating mixtures with 1-alkanols. This has been attributed to the strong dipole–dipole interactions between NMP molecules, characteristic of the investigated systems. Mixture structure is briefly studied in terms of the concentration–concentration structure factor.Key words: thermodynamics, NMP, organic solvent, self-association, dipole–dipole interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it