Hadi Mobasheri - Department of Chemical Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
Ebrahim Nemati Lay - Department of Chemical Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
Ehsan Sanjari - Department of Chemical Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran

The heat capacity of ionic liquids is of special importance in engineering applications being required in calculations of energy transfer and thermodynamics. In this study heat capacity of different types of ionic liquids are modeled by using an artificial neural network (ANN) based onback-propagation method. A reliable database including more than 3600 experimental data of heat capacity is used for testing and training of ANN. The designed neural network can predict the heat capacity of ionic liquids used in this work with average absolute relative deviation percent of 2.95.

Ionic Liquid, Heat Capacity, Neural Network, ANN