Modeling from Theory and Modeling from Data: Complementary or Alternative Approaches? The Case of Ionic Liquids.
In the field of ionic liquids (ILs), theory-driven modeling approaches aimed at the best fit for all available data by using a unique, and often nonlinear, model have been widely adopted to develop quantitative structure-property relationship (QSPR) models. In this context, we propose chemoinformatic and chemometric data-driven procedures that lead to QSPR soft models with local validity that are able to predict relevant physicochemical properties of ILs, such as viscosity, density, decomposition temperature, and conductivity. These models, which use readily available and easily interpretable VolSurf+ descriptors, represent an unexploited opportunity for experimentalists to model and predict the physicochemical properties of ILs in industrial R&D design.
Dipartimento di Scienze Chimiche Università di Catania Viale A. Doria 6 95125 Catania Italy.
Alessio
A
Paternò
Laboratorio di Chemiometria e Chemioinformatica Dipartimento di Chimica Università di Perugia Via Elce di Sotto 10 06123 Perugia Italy.
Laura
L
Goracci
Dipartimento di Scienze Chimiche Università di Catania Viale A. Doria 6 95125 Catania Italy.
Salvatore
S
Scire
Dipartimento di Scienze Chimiche Università di Catania Viale A. Doria 6 95125 Catania Italy.
Giuseppe
0000-0003-3505-1900
G
Musumarra
chemoinformatics; ionic liquids; molecular modeling; physicochemical properties; structure–activity relationships