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: | N1694 | |
|---|---|---|
| Name: | nonane, 1-butyl-3-methylimidazolium hexafluorophosphate | |
| Description: | nonane [MBIm]+[PF6]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C9H20.C8H15N2.F6P/c1-3-5-7-9-8-6-4-2;1-3-4-5-10-7-6-9(2)8-10;1-7(2,3,4,5)6/h3-9H2,1-2H3;6-8H,3-5H2,1-2H3;/q;+1;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.086 |
experimental value |
| 2.011543423421116 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.020967357142861 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |