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: | N4639 | |
|---|---|---|
| Name: | acetonitrile, 1-ethyl-3-methylimidazolium methylphosphonate | |
| Description: | acetonitrile [MEIm]+[(MeO)(H)PO2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C6H11N2.C2H3N.CH5O3P/c1-3-8-5-4-7(2)6-8;1-2-3;1-4-5(2)3/h4-6H,3H2,1-2H3;1H3;5H,1H3,(H,2,3)/q+1;;/p-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.29 |
experimental value |
| 2.690197607589586 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.245996897688348 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |