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: | N2032 | |
|---|---|---|
| Name: | tetrachloromethane, 1-ethyl-3-methylimidazolium nitrate | |
| Description: | tetrachloromethane [MEIm]+[NO3]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C6H11N2.CCl4.NO3/c1-3-8-5-4-7(2)6-8;2-1(3,4)5;2-1(3)4/h4-6H,3H2,1-2H3;;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.259 |
experimental value |
| 2.055131171332208 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.276989999999995 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |