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: | N5120 | |
|---|---|---|
| Name: | 1-chlorooctane, n-butyl-n-methylpyrrolidinium thiocyanate | |
| Description: | 1-chlorooctane [BMPyrr]+[SCN]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C9H20N.C8H17Cl.CHNS/c1-3-4-7-10(2)8-5-6-9-10;1-2-3-4-5-6-7-8-9;2-1-3/h3-9H2,1-2H3;2-8H2,1H3;3H/q+1;;/p-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.464791600787368 |
experimental value |
| 3.398350740561409 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.548346782908149 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |