Mixing Schemes in Ionic Liquid−H<sub>2</sub>O Systems: A Thermodynamic Study
Bibliographic record
Abstract
We studied the hydration characteristics of room-temperature ionic liquids (IL). We experimentally determined the excess chemical potentials,, the excess partial molar enthalpies,, and the excess partial molar entropies in IL−H 2 O systems at 25 °C. The ionic liquids studied were 1-butyl-3-methylimidazolium tetrafluoroborate ([bmim]BF 4 ) and the iodide ([bmim]I). From these data, the excess (integral) molar enthalpy and entropy, and, and the IL−IL enthalpic interaction,, were calculated. Using these thermodynamic data, we deduced the mixing schemes, or the “solution structures”, of IL−H 2 O systems. At infinite dilution IL dissociates in H 2 O, but the subsequent hydration is much weaker than for NaCl. As the concentration of IL increases, [bmim] + ions and the counteranions begin to attract each other up to a threshold mole fraction, x IL = 0.015 for [bmim]BF 4 and 0.013 for [bmim]I. At still higher mole fractions, IL ions start to organize themselves, directly or in an H 2 O-mediated manner. Eventually for x IL > 0.5−0.6, IL molecules form clusters of their own kind, as in their pure states. We show that, a third derivative of G, provided finer details than and, second derivatives, which in turn gave more detailed information than and, first derivative quantities.
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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) | 0.000 | 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 | 0.001 |
| 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".