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: | N100 | |
|---|---|---|
| Name: | 2,2,4-trimethylpentane, 4-(3-hydroxypropyl)-4-methylmorpholinium bis(trifluoromethylsulfonyl)imide | |
| Description: | 2,2,4-trimethylpentane [PrOHMMorp]+[(Tf)2N]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C8H18NO2.C8H18.C2F6NO4S2/c1-9(3-2-6-10)4-7-11-8-5-9;1-7(2)6-8(3,4)5;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8/h10H,2-8H2,1H3;7H,6H2,1-5H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 0.4999874727042632 |
experimental value |
| 1.364701273986227 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 0.6388962998622125 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |