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: | N2614 | |
|---|---|---|
| Name: | nonane, 1-ethyl-3-methylimidazolium diethylphosphate | |
| Description: | nonane [MEIm]+[E2PO4]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C9H20.C6H11N2.C4H11O4P/c1-3-5-7-9-8-6-4-2;1-3-8-5-4-7(2)6-8;1-3-7-9(5,6)8-4-2/h3-9H2,1-2H3;4-6H,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 |
|---|---|
| 2.550100395367722 |
experimental value |
| 2.127845435817446 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.487911669722092 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |