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:	N4511
	Name:	acetonitrile, 4-cyano-1-butylpyridinium bis(trifluoromethylsulfonyl)imide
	Description:	acetonitrile [4-CNBPy]+[(Tf)2N]-
	Labels:
	CAS:
	InChi Code:	InChI=1S/C10H13N2.C2F6NO4S2.C2H3N/c1-2-3-6-12-7-4-10(9-11)5-8-12;3-1(4,5)14(10,11)9-15(12,13)2(6,7)8;1-2-3/h4-5,7-8H,2-3,6H2,1H3;;1H3/q+1;-1;

Properties

logK: Gas-ionic liquid partition coefficient

Value	Source or prediction
3.231	experimental value
2.937212374982046	MLR: Multiple Linear Regression QSAR model for the gas-ionic liquid partition coefficient of organic solutes (MLR holdout predictions)
3.067341025202038	RF: Random Forest Regression QSAR model for gas-ionic liquid partition coefficient of organic solutes (RF holdout predictions)