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: | N2632 | |
|---|---|---|
| Name: | nonane, 4-methyl-n-butylpyridinium bis(trifluoromethylsulfonyl)imide | |
| Description: | nonane [4-MBPy]+[Tf2N]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H16N.C9H20.C2F6NO4S2/c1-3-4-7-11-8-5-10(2)6-9-11;1-3-5-7-9-8-6-4-2;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8/h5-6,8-9H,3-4,7H2,1-2H3;3-9H2,1-2H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.558 |
experimental value |
| 2.283108950988578 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.520250263106564 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |