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: | N6411 | |
|---|---|---|
| Name: | acetophenone, n-butyl-n-methylpyrrolidinium thiocyanate | |
| Description: | acetophenone [BMPyrr]+[SCN]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C9H20N.C8H8O.CHNS/c1-3-4-7-10(2)8-5-6-9-10;1-7(9)8-5-3-2-4-6-8;2-1-3/h3-9H2,1-2H3;2-6H,1H3;3H/q+1;;/p-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 5.233744735457923 |
experimental value |
| 5.032235252107894 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR holdout predictions) |
| 5.365601986690691 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF holdout predictions) |