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: | N3838 | |
|---|---|---|
| Name: | 2-pentanone, 4-methyl-n-butylpyridinium thiocyanate | |
| Description: | 2-pentanone [4-MBPy]+[SCN]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H16N.C5H10O.CHNS/c1-3-4-7-11-8-5-10(2)6-9-11;1-3-4-5(2)6;2-1-3/h5-6,8-9H,3-4,7H2,1-2H3;3-4H2,1-2H3;3H/q+1;;/p-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.981 |
experimental value |
| 2.69467735825437 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.981308535961528 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |