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: | N6142 | |
|---|---|---|
| Name: | water, 4-ethyl-4-methylmorpholinium dicyanamide | |
| Description: | water [EMMorp]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C7H16NO.C2N3.H2O/c1-3-8(2)4-6-9-7-5-8;3-1-5-2-4;/h3-7H2,1-2H3;;1H2/q+1;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 4.170312468461404 |
experimental value |
| 2.518840788298966 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.924631614168418 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |