The Ionic Liquid Property Explorer: An Extensive Library of Task-Specific Solvents

• Main Authors: Vishwesh Venkatraman, Sigvart Evjen, Kallidanthiyil Chellappan Lethesh
• Format: Article
• Language: English
• Published: MDPI AG 2019-06-01
• Series: Data
• Subjects: ionic liquids; machine learning; database; properties; combinatorial screening
• Online Access: https://www.mdpi.com/2306-5729/4/2/88

Ionic liquids have a broad spectrum of applications ranging from gas separation to sensors and pharmaceuticals. Rational selection of the constituent ions is key to achieving tailor-made materials with functional properties. To facilitate the discovery of new ionic liquids for sustainable applications, we have created a virtual library of over 8 million synthetically feasible ionic liquids. Each structure has been evaluated for their-task suitability using data-driven statistical models calculated for 12 highly relevant properties: melting point, thermal decomposition, glass transition, heat capacity, viscosity, density, cytotoxicity, CO<inline-formula> <math display="inline"> <semantics> <msub> <mrow></mrow> <mn>2</mn> </msub> </semantics> </math> </inline-formula> solubility, surface tension, and electrical and thermal conductivity. For comparison, values of six properties computed using quantum chemistry based equilibrium thermodynamics COSMO-RS methods are also provided. We believe the data set will be useful for future efforts directed towards targeted synthesis and optimization.