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: | N3943 | |
|---|---|---|
| Name: | methanol, 1-hydroxyethyl-1-methylmorpholinium dicyanamide | |
| Description: | methanol [EtOHMMorp]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C7H16NO2.C2N3.CH4O/c1-8(2-5-9)3-6-10-7-4-8;3-1-5-2-4;1-2/h9H,2-7H2,1H3;;2H,1H3/q+1;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.018272463651431 |
experimental value |
| 2.504941313490572 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.999157886738918 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |