(Invited) Ionic Fluids Containing Both Strongly and Weakly Interacting Ions of the Same Charge Have Unique Ionic and Thus Chemical Environments As a Function of Ion Concentration
Bibliographic record
Abstract
Liquid multi-ion systems or Double Salt Ionic Liquids (DSILs; salts composed of more than two types of ions, liquid at low temperature (below 100 °C),[1]) made by combining two or more salts can exhibit charge ordering and interactions not found in the parent salts, leading to new sets of properties. This effect is investigated here by examining liquid systems made by mixing two miscible ionic liquids comprised of a single cation, 1-ethyl-3-methylimidazolium ([C 2 mim] + ), and two anions with very different properties, acetate ([OAc] - ) and bis(trifluoromethylsulfonyl)imide ([NTf 2 ] - ), namely [C 2 mim][OAc] x [NTf 2 ] (1-x) , and made by dissolving a crystalline salt, ammonium acetate ([NH 4 ][OAc]), in the ionic liquid [C 2 mim][OAc] in their miscible range, namely [NH 4 ] x [C 2 mim] (1-x) [OAc] (0 ≤ x ≤ 0.58). Through NMR and FT-IR spectroscopic analysis, we have shown that the electrostatic interactions present are quite different from those in the parent salts. We attribute this to the unique charge ordering arising from the ability of [OAc] - to form complexes with [C 2 mim] + ions by drawing [C 2 mim] + ions away from the less basic [NTf 2 ] - ions or the ability of [NH 4 ] + cation to form complexes with [OAc] - ions by “stealing” [OAc] - from the less acidic [C 2 mim] + ions. Solubility studies with various kinds of organic solutes ( e.g. , EtOAc, H 2 O, chloroform, benzene, tetrahydrofuran) and active pharmaceutical ingredients (ibuprofen and diphenhydramine) indicate that the solubilities of these solutes in the DSILs show dramatic, non-linear trends as a function of ion concentration, demonstrating that solubility of selected solutes can be finely tuned via changes in the ionic compositions. These kinds of DSILs provide potential solvent systems with unique and tunable properties to be used in the electrochemical and separation fields. References [1]. G. Chatel, J. F. B. Pereira, V. Debbeti, H. Wang and R. D. Rogers, Green Chem. , 16 , 2051 (2014).
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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 | 0.001 |
| 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 | 0.000 |
| 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".