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Estimation of NRTL Binary Parameters in the Sulfur Compounds Extractive Process by Ionic Liquids Using Genetic Intelligent Optimization Algorithm

Publish Year: 1401
Type: Conference paper
Language: English
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THERMODYNAMICS06_012

Index date: 18 June 2022

Estimation of NRTL Binary Parameters in the Sulfur Compounds Extractive Process by Ionic Liquids Using Genetic Intelligent Optimization Algorithm abstract

In this work using Liquid–liquid equilibrium experimental data of ternery system by ionic liquid (1-ethyl-3-methylimidazolium ethylsulfate +thiophene+hydrocarbons) has been estimated NRTL binary parameters using genetic intelligent optimization algorithm as a high-precision model for investigating phase equilibria and separation of sulfur compounds from liquid hydrocarbons. The NRTL activity equations were used to correlate the experimental data, and the binary interaction parameters were determined. finally the experimental data were correlated using the NRTL equation with RMSE 0.0061651 and 0.024715 for hydrocarbons of the n-Nonane and n-Decane, respectivly and the NRTL binary interaction parameters have been estimated. The phase diagrams for the ternary two phsae system (LLE) have been reported.

Estimation of NRTL Binary Parameters in the Sulfur Compounds Extractive Process by Ionic Liquids Using Genetic Intelligent Optimization Algorithm Keywords:

Estimation of NRTL Binary Parameters in the Sulfur Compounds Extractive Process by Ionic Liquids Using Genetic Intelligent Optimization Algorithm authors

A Haghani

Chemical Engineering Faculty, Sahand University of Technology, P.O. Box ۵۱۳۳۵-۱۹۹۶, Sahand New Town, Tabriz, Iran

A Tavakoli

`Chemical Engineering Faculty, Sahand University of Technology, P.O. Box ۵۱۳۳۵-۱۹۹۶, Sahand New Town, Tabriz, Iran