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: | N3242 | |
|---|---|---|
| Name: | propanone, n-butyl-n-methylpyrrolidinium tricyanomethanide | |
| Description: | propanone [BMPyrr]+[C(CN)3]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C9H20N.C4N3.C3H6O/c1-3-4-7-10(2)8-5-6-9-10;5-1-4(2-6)3-7;1-3(2)4/h3-9H2,1-2H3;;1-2H3/q+1;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.778 |
experimental value |
| 2.535024786009568 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.689589785533735 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |