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: | N2392 | |
|---|---|---|
| Name: | methanol, 1,3-di(hexyloxymethyl)imidazolium bis(trifluoromethylsulfonyl)imide | |
| Description: | methanol [(Hexom)2Im]+[Tf2N]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C17H33N2O2.C2F6NO4S2.CH4O/c1-3-5-7-9-13-20-16-18-11-12-19(15-18)17-21-14-10-8-6-4-2;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8;1-2/h11-12,15H,3-10,13-14,16-17H2,1-2H3;;2H,1H3/q+1;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.439 |
experimental value |
| 2.766802342023155 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.421860661087437 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |