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: | N914 | |
|---|---|---|
| Name: | heptane, 3-methyl-n-butylpyridinium triflate | |
| Description: | heptane [3-MBPy]+[Trif]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H16N.C7H16.CHF3O3S/c1-3-4-7-11-8-5-6-10(2)9-11;1-3-5-7-6-4-2;2-1(3,4)8(5,6)7/h5-6,8-9H,3-4,7H2,1-2H3;3-7H2,1-2H3;(H,5,6,7)/q+1;;/p-1 |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 1.626 |
experimental value |
| 1.506869718087006 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 1.594976668528059 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |