Molar excess enthalpies for some systems containing the OH and (or) O groups in the same or in different molecules
Bibliographic record
Abstract
In this work, HmE data at 298.15 K for the systems 1-nonanol + n-C12; 1-nonanol + n-C14; 1-hexanol + 3,6,9-trioxaundecane; and 2-(2-butoxyethoxyethanol) + n-C7 are reported. Measurements were carried out with a standard Calvet-type microcalorimeter. Molar excess functions, including enthalpies and entropies, are carefully examined to report on the main features of the studied solutions. Dipoledipole interactions between ether molecules are, therefore, of great importance in both 1-alkanols + polyoxaalkanes mixtures and between hydroxyether molecules in alkoxy ethanols + n-alkanes systems. In the second case, it has been attributed to the existence of intramolecular H-bonds in alkoxy ethanols as well as to their higher effective-dipole moment in comparison to that of homologous 1-alkanols. DISQUAC is the only model that can be used to accurately represent thermodynamic functions (except molar excess volumes, VmE) of all of the solutions under study. UNIFAC underestimates dipoledipole interactions in 1-alkanols + polyoxaalkanes and alkoxyethanols + n-alkanes systems. In exchange, the self-association of the alcohol is overestimated in mixtures of 1-nonanol with n-alkanes. Currently, the ERAS model can only be used to examine these solutions. The variation of the VmE with the size of the n-alkanes is well described. Key words: excess functions, OH group, O group, interactions, models.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".