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: | N6422 | |
|---|---|---|
| Name: | acetophenone, n-butyl-n-methylpiperidinium bis(trifluoromethylsulfonyl)imide | |
| Description: | acetophenone [BMPip]+[(Tf)2N]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H22N.C8H8O.C2F6NO4S2/c1-3-4-8-11(2)9-6-5-7-10-11;1-7(9)8-5-3-2-4-6-8;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8/h3-10H2,1-2H3;2-6H,1H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 5.272310742983316 |
experimental value |
| 5.25832350120084 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 5.280140843936988 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |