Modeling from Theory and Modeling from Data: Complementary or Alternative Approaches? The Case of Ionic Liquids. Issue 1 (9th January 2017)

• Record Type: Journal Article
• Authors: Paternò, Alessio; Goracci, Laura; Scire, Salvatore; Musumarra, Giuseppe
• Is Part Of: ChemistryOpen. Volume 6:Issue 1(2017)
• Page Start: 90
• Page End: 101
• Publication Date: 2017-01-09
• Subjects: chemoinformatics -- ionic liquids -- molecular modeling -- physicochemical properties -- structure–activity relationships; Chemistry -- Periodicals; 540; 540.5
• DOI: 10.1002/open.201600119
• Languages: English
• ISSNs: 2191-1363

Abstract

Abstract: 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. Abstract : Practical models : Quantitative structure–property relationship (QSPR) soft models by using simple equations and readily available descriptors are adopted to predict the physicochemical properties of ionic liquids (ILs) and provide new opportunities for experimentalists in industrial R&D design.