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: | N3512 | |
|---|---|---|
| Name: | 1-octyne, 4-methyl-n-butylpyridinium dicyanamide | |
| Description: | 1-octyne [4-MBPy]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H16N.C8H14.C2N3/c1-3-4-7-11-8-5-10(2)6-9-11;1-3-5-7-8-6-4-2;3-1-5-2-4/h5-6,8-9H,3-4,7H2,1-2H3;1H,4-8H2,2H3;/q+1;;-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.872448497913122 |
experimental value |
| 2.75164097225697 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.86846500484124 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |