Relative Hydrophobicity and Hydrophilicity of Some “Ionic Liquid” Anions Determined by the 1-Propanol Probing Methodology: A Differential Thermodynamic Approach
Bibliographic record
Abstract
The excess partial molar enthalpy of 1-propanol (1P), H(E) (1P), was experimentally measured in ternary 1P-[NaPF(6), NaCF(3)SO(3) (OTF) or NaN(SO(2)CF(3))(2) (TFSI)]-H(2)O system. From the H(E) (1P), the enthalpic 1P-1P interaction function, H(E) (1P-1P), which is the compositional derivative of H(E) (1P), was evaluated graphically. On addition of the Na salt, the x(1P)-dependence pattern of H(E) (1P-1P) showed a characteristic change. This induced change is used as a probe to elucidate the effect of the sample Na-salt on H(2)O. Because we know the effect of Na(+) from our previous work, we show that each anion works as an amphiphile with hydrophobic and hydrophilic effects. Furthermore, the present method can quantify its relative hydrophobicity and hydrophilicity separately. The results indicate that the relative hydrophobicity ranking was in the order of TFSI(-) > PF(6-) approximately OTF(-), and the hydrophilicity TFSI(-) > PF6(- )> OTF-. Namely, TFSI- is the strongest amphiphile with the strongest hydrophobicity and the strongest hydrophilicity among the ionic liquid (IL) anions studied here. Using our earlier similar studies for normal ions, we map their relative hydrophobicity/hydrophilicity scales on a two-dimensional map together with those of the IL ions. The resulting map shows that the typical constituent ions for "ionic liquids" are strong amphiphiles; with more strongly hydrophobic and more strongly hydrophilic propensities than normal ions. Although the number of data points is limited, the melting points of ionic liquids consisting of TFSI(-) with the strongest hydrophobicity and the strongest hydrophilicity within the anions studied here are the lowest.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".