SCI和EI收录∣中国化工学会会刊

›› 2016, Vol. 24 ›› Issue (12): 1761-1771.DOI: 10.1016/j.cjche.2016.05.003

• Chemical Engineering Thermodynamics • 上一篇    下一篇

Statistical mechanics and artificial intelligence to model the thermodynamic properties of pure and mixture of ionic liquids

Fakhri Yousefi, Zeynab Amoozandeh   

  1. Department of Chemistry, Yasouj University, Yasouj 75914-353, Iran
  • 收稿日期:2016-01-17 修回日期:2016-05-09 出版日期:2016-12-28 发布日期:2017-01-04
  • 通讯作者: Fakhri Yousefi,E-mail address:fyousefi@mail.yu.ac.ir
  • 基金资助:
    Supported by the Yasouj University.

Statistical mechanics and artificial intelligence to model the thermodynamic properties of pure and mixture of ionic liquids

Fakhri Yousefi, Zeynab Amoozandeh   

  1. Department of Chemistry, Yasouj University, Yasouj 75914-353, Iran
  • Received:2016-01-17 Revised:2016-05-09 Online:2016-12-28 Published:2017-01-04
  • Supported by:
    Supported by the Yasouj University.

摘要: In this paper, the volumetric properties of pure and mixture of ionic liquids are predicted using the developed statistical mechanical equation of state in different temperatures, pressures and mole fractions. The temperature dependent parameters of the equation of state have been calculated using corresponding state correlation based on only the density at 298.15 K as scaling constants. The obtained mean of deviations of modified equation of state for density of all pure ionic liquids for 1662 data points was 0.25%. In addition, the performance of the artificial neural network (ANN) with principle component analysis (PCA) based on back propagation training with 28 neurons in hidden layer for predicting of behavior of binary mixtures of ionic liquids was investigated. The AADs of a collection of 568 data points for all binary systems using the EOS and the ANN at various temperatures and mole fractions are 1.03% and 0.68%, respectively. Moreover, the excess molar volume of all binary mixtures is predicted using obtained densities of EOS and ANN, and the results show that these properties have good agreement with literature.

关键词: Ionic liquids, Thermodynamic properties, Equation of state, Artificial neural network

Abstract: In this paper, the volumetric properties of pure and mixture of ionic liquids are predicted using the developed statistical mechanical equation of state in different temperatures, pressures and mole fractions. The temperature dependent parameters of the equation of state have been calculated using corresponding state correlation based on only the density at 298.15 K as scaling constants. The obtained mean of deviations of modified equation of state for density of all pure ionic liquids for 1662 data points was 0.25%. In addition, the performance of the artificial neural network (ANN) with principle component analysis (PCA) based on back propagation training with 28 neurons in hidden layer for predicting of behavior of binary mixtures of ionic liquids was investigated. The AADs of a collection of 568 data points for all binary systems using the EOS and the ANN at various temperatures and mole fractions are 1.03% and 0.68%, respectively. Moreover, the excess molar volume of all binary mixtures is predicted using obtained densities of EOS and ANN, and the results show that these properties have good agreement with literature.

Key words: Ionic liquids, Thermodynamic properties, Equation of state, Artificial neural network