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: | N2353 | |
|---|---|---|
| Name: | propanone, n-butyl-n-methylpiperidinium thiocyanate | |
| Description: | propanone [BMPip]+[SCN]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H22N.C3H6O.CHNS/c1-3-4-8-11(2)9-6-5-7-10-11;1-3(2)4;2-1-3/h3-10H2,1-2H3;1-2H3;3H/q+1;;/p-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.421 |
experimental value |
| 2.349640351596287 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.450717485469143 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |