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: | N3583 | |
|---|---|---|
| Name: | tetrachloromethane, 1-ethyl-3-methylimidazolium diethylphosphate | |
| Description: | tetrachloromethane [MEIm]+[E2PO4]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C6H11N2.C4H11O4P.CCl4/c1-3-8-5-4-7(2)6-8;1-3-7-9(5,6)8-4-2;2-1(3,4)5/h4-6H,3H2,1-2H3;3-4H2,1-2H3,(H,5,6);/q+1;;/p-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.896155114104317 |
experimental value |
| 2.225715038911424 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.743051092763685 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |