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: | N4356 | |
|---|---|---|
| Name: | acetonitrile, 1,2,3-tris(diethylamino)cyclopropenylium dicyanamide | |
| Description: | acetonitrile [TDC]+[N(CN)2]- | |
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C15H30N3.C2N3.C2H3N/c1-7-16(8-2)13-14(17(9-3)10-4)15(13)18(11-5)12-6;3-1-5-2-4;1-2-3/h7-12H2,1-6H3;;1H3/q+1;-1; |
Properties
logK: Gas-ionic liquid partition coefficient
| Value | Source or prediction |
|---|---|
| 3.17146496812669 |
experimental value |
| 3.031522060491671 |
MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR holdout predictions) |
| 2.90321642356875 |
RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF holdout predictions) |