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: | N930 | |
|---|---|---|
| Name: | diisopropyl ether, 4-cyano-1-butylpyridinium bis(trifluoromethylsulfonyl)imide | |
| Description: | diisopropyl ether [4-CNBPy]+[(Tf)2N]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H13N2.C6H14O.C2F6NO4S2/c1-2-3-6-12-7-4-10(9-11)5-8-12;1-5(2)7-6(3)4;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8/h4-5,7-8H,2-3,6H2,1H3;5-6H,1-4H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 1.636 |
experimental value |
| 1.910034992467238 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 1.703210118014499 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |