Excess partial molar entropy of alkane-mono-ols in aqueous solutions at 25°C
Bibliographic record
Abstract
In the preceding paper, we reported the values of model-free chemical potentials for aqueous methanol, ethanol, 1-propanol, 2-propanol, 1-butanol, and 1-hexanol at 25°C over the entire compositional region. Using alcohol excess partial molar enthalpies, HEAL, determined earlier in this laboratory (Can. J. Chem. 74, 713 (1996)), we have calculated excess partial molar entropies for the alcohols, SEAL, where AL stands for an alcohol. We then calculated, numerically, the entropic interaction, SEALAL = N([Formula: see text]SEAL/[Formula: see text]nAL)p,T,nW, where nAL is the amount of AL, nW is the amount of H2O, and N is the total amount of solution. SEALAL signifies the effect of addition of AL upon the entropic situation of existing AL in solution. Using these quantities, the mixing schemes in aqueous alcohols have been studied. The earlier conclusions, which used HEAL and HEALAL alone, are confirmed. Furthermore, the order of the relative hydrophobic nature of alcohols is established from the behaviour of SEALAL and of HEALAL as methanol < ethanol < 2-propanol < 1-propanol. Key Words: aqueous alcohols, excess partial molar entropies, entropic interaction mixing schemes, hydrophobicity ranking.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".