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: | N4750 | |
|---|---|---|
| Name: | alpha-methylstyrene, 1-hydroxyethyl-1-methylmorpholinium dicyanamide | |
| Description: | alpha-methylstyrene [EtOHMMorp]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C9H10.C7H16NO2.C2N3/c1-8(2)9-6-4-3-5-7-9;1-8(2-5-9)3-6-10-7-4-8;3-1-5-2-4/h3-7H,1H2,2H3;9H,2-7H2,1H3;/q;+1;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.32878713934075 |
experimental value |
| 3.688800366189872 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.455097412326436 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |