Interactions of Na-Salts and 1-Propanol in 1-Propanol−Na-Salt−H<sub>2</sub>O Systems: Toward an Understanding the Hofmeister Series (IV)
Bibliographic record
Abstract
The excess chemical potential of 1-propanol (1P), muE1P, was evaluated in ternary 1P-Na-salt(S)-H2O at 25 degrees C. The counter anions of the Na-salts studied are SO42-, F-, Cl-, I-, and ClO4-. The effect of the anion on muE1P follows the Hofmeister ranking, in that the more kosmotropic ions make the muE1P value more positive. We then evaluate the effect of the Na-salt (S) on muE1P, the 1P-S interaction in terms of excess chemical potential, at a semi-infinite dilution. The results indicate that the 1P-S interaction in terms of excess chemical potential is unfavorable (repulsive) for all of the ions studied. The degree of repulsive interaction decreases in the order of the Hofmeister ranking from the kosmotropic to the chaotropic end. Namely, salting-out samples make the excess part of the chemical potential of 1P more unfavorable, while the salting-in counterparts make it less unfavorable. From earlier calorimetric studies on the same ternary systems, the enthalpic 1P-S interaction function, HE 1P-S , was calculated. Hence, the entropy analogue, S1P-S , was also obtained, and a detailed thermodynamic signature of 1P-S interactions became available. This revealed that both HE 1P-S and SE 1P-S decrease from the kosmotropic ion to the middle of the ranking (Cl-), whereupon they turn to increase toward the chaotropic end. Hence, the build up of unfavorable 1P-S interactions in Hofmeister salts (signified by muE1P) relies on a pronounced enthalpy-entropy compensation, which must be accounted for in attempts to understand the molecular mechanisms underpinning Hofmeister effects.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".