Temperature dependence investigations of molecular interactions and excess thermodynamic parameters of binary mixtures of ionic liquids and water using Flory's statistical theory
Bibliographic record
Abstract
Abstract Flory's Statistical Theory (FST) has been applied to investigate excess thermodynamical parameters viz., excess enthalpy, excess entropy, and excess Gibbs free energy for eight binary mixtures of ionic liquids and water at different concentration and temperatures. The concentration and temperature dependent variations of excess enthalpy suggest that ionic liquid mixtures exhibit an endothermic nature and the presence of weak dispersive forces among their constituents. The positive excess Gibbs free energy of mixing points out that the pure components do not mix thoroughly for the systems under study. Overall, these binary systems are thermodynamically unfavorable suggesting that the mixing of ionic liquids and water is not energetically favored or spontaneous. Experimental molar volumes are compared with those calculated using FST and these values show excellent agreement. It affirms the validity of FST's application to these systems. Additionally, some partial properties have also been determined to explore the solute‐solvent interactions. The Redlich‐Kister (R‐K) polynomial model has been applied to excess thermodynamical parameters The high R 2 values and low standard deviation values confirm the validity of fitting the RK polynomial model to the functions obtained using FST of liquids for these systems within the given temperature range.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".