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: | N3875 | |
|---|---|---|
| Name: | acetonitrile, 1-allyl-3-methylimidazolium dicyanamide | |
| Description: | acetonitrile [AllMIm]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C7H11N2.C2N3.C2H3N/c1-3-4-9-6-5-8(2)7-9;3-1-5-2-4;1-2-3/h3,5-7H,1,4H2,2H3;;1H3/q+1;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.996 |
experimental value |
| 2.801473416819531 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.044154743423582 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |