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: | N49 | |
|---|---|---|
| Name: | diisopropyl ether, 1-hydroxyethyl-1-methylmorpholinium dicyanamide | |
| Description: | diisopropyl ether [EtOHMMorp]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C7H16NO2.C6H14O.C2N3/c1-8(2-5-9)3-6-10-7-4-8;1-5(2)7-6(3)4;3-1-5-2-4/h9H,2-7H2,1H3;5-6H,1-4H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 0.225 |
experimental value |
| 1.764029296564912 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 0.3988802226842902 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |