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: | N4230 | |
|---|---|---|
| Name: | thiophene, 1-hexyl-3-methylimidazolium tetracyanoborate | |
| Description: | thiophene [MHIm]+[B(CN)4]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C10H19N2.C4BN4.C4H4S/c1-3-4-5-6-7-12-9-8-11(2)10-12;6-1-5(2-7,3-8)4-9;1-2-4-5-3-1/h8-10H,3-7H2,1-2H3;;1-4H/q+1;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.123 |
experimental value |
| 2.950302766579646 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 3.109701642658417 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |