Toots, K. M.; Sild, S.; Leis, J.; Acree, W. E.; Maran, U. A multicomponent QSPR approach to describe and predict gas-ionic liquid distribution of organic solutes using machine learning. J. Mol. Liq. 2025, 436, 128184.
Compound
| ID: | N4915 | |
|---|---|---|
| Name: | undecane, n-hexyl-n-methylpyrrolidinium bis(trifluoromethylsulfonyl)imide | |
| Description: | undecane [C6MPyrr]+[Tf2N]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C11H24N.C11H24.C2F6NO4S2/c1-3-4-5-6-9-12(2)10-7-8-11-12;1-3-5-7-9-11-10-8-6-4-2;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8/h3-11H2,1-2H3;3-11H2,1-2H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.39 |
experimental value |
| 3.054730012288898 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.441549066215031 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |