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: | N5747 | |
|---|---|---|
| Name: | styrene, trihexyl(tetradecyl)phosphonium tricyanomethanide | |
| Description: | styrene [H3TdP]+[C(CN)3]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C32H68P.C8H8.C4N3/c1-5-9-13-17-18-19-20-21-22-23-24-28-32-33(29-25-14-10-6-2,30-26-15-11-7-3)31-27-16-12-8-4;1-2-8-6-4-3-5-7-8;5-1-4(2-6)3-7/h5-32H2,1-4H3;2-7H,1H2;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.778933339110067 |
experimental value |
| 3.820093437707799 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.929566157894658 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |