A simple group contribution correlation for the prediction of ionic liquid heat capacities at different temperatures

The heat capacities of pure ionic liquids (ILs) are among the thermophysical properties that are required for certain engineering calculations and designs. In this study, a simple correlation is presented for the prediction of the heat capacities of pure ionic liquids. This correlation is a temperature-dependent relation that uses temperature, molecular weight and the number of atoms (such as carbon, hydrogen, oxygen, nitrogen, etc.) in the structure of the IL as input parameters. A dataset of approximately 128 different ILs, consisting of 4822 data points, was used to develop and validate this general correlation, covering a temperature range from 190 to 663 K. Nearly three-quarters of the data were used for optimization and a quarter for validation. The resulting correlation gives good estimations for heat capacities, while having a number of advantages over previous literatures methods. These advantages include (a) being very simple; (b) not requiring any experimental data as input parameters; (c) being more global than previous literature models by having been constructed over a larger databank of ionic liquids; (d) being accurate. The average absolute relative deviation (AARD%) was calculated to be 5.8% for the optimization dataset, and 5.6% for the validation dataset. This is smaller than what is obtained for the literature atomic-contribution methods proposed by Farahani et al. and Sattari et al., with AARD% values of 14.2% and 6.6%, respectively, based on the validation dataset of this study.