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: | N99 | |
|---|---|---|
| Name: | diethyl ether, 1-hydroxyethyl-1-methylmorpholinium dicyanamide | |
| Description: | diethyl ether [EtOHMMorp]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C7H16NO2.C4H10O.C2N3/c1-8(2-5-9)3-6-10-7-4-8;1-3-5-4-2;3-1-5-2-4/h9H,2-7H2,1H3;3-4H2,1-2H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 0.497 |
experimental value |
| 1.698737841948637 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 0.6666379861738336 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |