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: | N3449 | |
|---|---|---|
| Name: | acetonitrile, n,n,n',n'-tetramethyl-n,n'-diisopropyl-1,9-nonanediaminium bis(trifluoromethylsulfonyl)imide | |
| Description: | acetonitrile [C1,9(M2iPAm)2]+[(Tf)2N]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C19H44N2.C2F6NO4S2.C2H3N/c1-18(2)20(5,6)16-14-12-10-9-11-13-15-17-21(7,8)19(3)4;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8;1-2-3/h18-19H,9-17H2,1-8H3;;1H3/q+2;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 2.852 |
experimental value |
| 3.19345024061173 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR training predictions) |
| 2.900983184949431 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF training predictions) |