On the Correlation of the Activity Coefficients in Aqueous Electrolyte Solutions Using the K-MSA Model
Bibliographic record
Abstract
The objective of this work is to extend the Kelvin mean spherical approximation (K-MSA) model to correlate the mean and individual ionic activity coefficients for symmetric and asymmetric electrolyte solutions at different concentrations and at different temperatures. Revised values of the parameters for the mean and individual ionic activity coefficients of 1:1 electrolytes and new values of the parameters for the mean ionic activity coefficients of asymmetric electrolytes are presented. The effect of the short-range electrostatic term ( P n ) at different size ratios of the ions is examined. Assuming a constant anion diameter and a composition-dependent diameter for the cation, the K-MSA model gives realistic cation-hydrated diameters, in comparison with their crystallographic Pauling diameters. Notably, for both symmetric and asymmetric electrolytes, the like and unlike ionic radial distribution function at contact value are positive over all of the concentration and temperature ranges studied. The results obtained from the K-MSA model compare favorably with those obtained from the Boublik−Mansoori−Carnahan−Starling−Leland mean spherical approximation and Pitzer models for the mean ionic activity coefficients and with those obtained with the Khoshkbarchi−Vera model for the individual ionic activity coefficients.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".