Group Contribution Estimation of Ionic Liquid Melting Points: Critical Evaluation and Refinement of Existing Models

Abstract

While several group contribution method (GCM) models have been developed in recent years for the prediction of ionic liquid (IL) properties, some challenges exist in their effective application. Firstly, the models have been developed and tested based on different datasets; therefore, direct comparison based on reported statistical measures is not reliable. Secondly, many of the existing models are limited in the range of ILs for which they can be used due to the lack of functional group parameters. In this paper, we examine two of the most diverse GCMs for the estimation of IL melting point; a key property in the selection and design of ILs for materials and energy applications. A comprehensive database consisting of over 1300 data points for 933 unique ILs, has been compiled and used to critically evaluate the two GCMs. One of the GCMs has been refined by introducing new functional groups and reparametrized to give improved performance for melting point estimation over a wider range of ILs. This work will aid in the targeted design of ILs for materials and energy applications.

Thermal Conductivities of NTf2-Based Ionic Liquids: Experimental Measurement and Prediction via Group Contribution Methods

“…However, it may be possible that the observed trend in thermal conduction with chain length follows similar trends as observed for the dependence of the melting point on chain length, that is, decreasing to a minimum with increasing chain length, followed by an increase on further increasing the chain length. 14,71 Similar trends have also been observed for density, 72 which appears to have a quadratic relationship with temperature. As the alkyl chain length increases, initially, the density decreases, primarily due to the looser packing of the alkyl chain.…”

“…It has been well known that the distribution of alkyl chains around the cation core has an effect on various thermophysical properties. ,, Comparing the chemical structures of various ILs, it is possible to see that more symmetric cations, or cations with more alkyl chains evenly distributed around the core, exhibit higher thermal conductivities at a given temperature. This can be seen in particular in the ammonium- and phosphonium-based ILs, exhibiting some of the highest thermal conductivities in the dataset.…”

“…One of the earliest GCMs was put forward by Joback and Reid . Today, GCMs are being used for the estimation of various properties, from critical temperature and pressure to melting point, ,, heat capacity, , density, and electrical conductivity . The fact that this approach relies on certain fundamental building blocks makes it easy to adapt to datasets with different properties.…”

“…Some properties, such as melting point and density, have been studied in depth and have large databases available already. 14,15 On the other hand, data for many other thermophysical properties are relatively scarce. Thermal conductivity is one such property, which also holds significant industrial importance.…”

“…With respect to industrial applications, such models can facilitate in silico screening of ILs to greatly reduce the costs involved in researching, synthesizing, and analyzing potential ILs. Some properties, such as melting point and density, have been studied in depth and have large databases available already. , On the other hand, data for many other thermophysical properties are relatively scarce. Thermal conductivity is one such property, which also holds significant industrial importance.…”