A new model for prediction of binary mixture of ionic liquids plus water density using artificial neural network

作者：Najafi Marghmaleki Adel; Khosravi Nikou Mohammad Reza^*; Barati Harooni Ali

来源：Journal of Molecular Liquids, 2016, 220: 232-237.

DOI：10.1016/j.molliq.2016.04.085

• Ionic liquid
• Density
• Multilayer perceptron
• Radial basis function

This study highlights the application of artificial neural network for prediction of density values in a binary mixture of water and ionic liquids at different temperature for different imidazolium-based ionic liquids. Two intelligent models named multilayer perceptron model and radial basis function model were developed and the accuracy of two models was examined by different graphical and statistical methods. The input parameters were temperature, water/ionic liquid ratio, molecular weight, critical temperature, critical pressure and boiling point temperature of ionic liquids and the model output was density. The molecular weight, critical temperature, critical pressure and boiling point temperature were used to discriminate among different ionic liquids. Results showed that the both models are accurate and effective in prediction of density of ionic liquid + water mixture. However, based on graphical and statistical representations, the multilayer perceptron model exhibits better performance and is superior compared to radial basis function model.

• 出版日期2016-8
• 单位中国石油大学（北京）