Ionic liquids (ILs), being related to the design of new environmentally friendly solvents, are
widely considered for applications within the “green chemistry” concept. Due to their unique …

The unique physicochemical properties, flexible structural tunability, and giant chemical
space of ionic liquids (ILs) provide them a great opportunity to match different target …

In this work, a nonlinear model that integrates the group contribution (GC) method with a
well-known machine learning algorithm, ie, artificial neural network (ANN), is proposed to …

Using the molecular functional group, two alternative models for predicting the dynamic
viscosity of ionic liquids (ILs) as function of temperature are presented. The group …

Ionic liquids (ILs) have attracted a great deal of attention as vital compounds that are widely
used in various industries, such as the chemical and petroleum industries. Therefore …

In this study, we developed two machine learning models:-support vector machine (SVM)
and artificial neural network (ANN)-to correlate ionic conductivity of pure ionic liquids based …

The ability to predict the phase equilibria behavior is of crucial relevance in the early design
stage of biphasic liquid-liquid systems. Ionic liquid-based aqueous biphasic systems (IL …

In this paper, we present three regression models developed for predicting electrical
conductivity, viscosity, and density of ionic liquids. Combining these machine learning …

Ionic liquids are compounds with interesting physical and chemical properties that can be
applied to a wide variety of processes. The knowledge of their thermodynamic properties is …

The incorporation of ionic liquids (ILs) into dielectric elastomer composites has attracted
significant interest due to their potential applications in soft actuators and optical devices …