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Article Navigation >  Green Energy&Environment  > 2019  >  4(2): 154-165
Zhen Song, Xinxin Li, He Chao, Fan Mo, Teng Zhou, Hongye Cheng, Lifang Chen, Zhiwen Qi. Computer-aided ionic liquid design for alkane/cycloalkane extractive distillation process. Green Energy&Environment, 2019, 4(2): 154-165. doi: 10.1016/j.gee.2018.12.001
Citation: Zhen Song, Xinxin Li, He Chao, Fan Mo, Teng Zhou, Hongye Cheng, Lifang Chen, Zhiwen Qi. Computer-aided ionic liquid design for alkane/cycloalkane extractive distillation process. Green Energy&Environment, 2019, 4(2): 154-165. doi: 10.1016/j.gee.2018.12.001
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Computer-aided ionic liquid design for alkane/cycloalkane extractive distillation process

doi: 10.1016/j.gee.2018.12.001
  • a.

    State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China

  • b.

    Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany

More Information
  • Corresponding author: E-mail address: lchen@ecust.edu.cn (Lifang Chen); E-mail address: zwqi@ecust.edu.cn (Zhiwen Qi)
  • Received date 07 November 2018, Accepted date 04 December 2018, RevRecd date 25 November 2018, Available online 12 December 2018, Publish date 30 April 2019,
    Abstract
  • A computer-aided ionic liquid design (CAILD) study is presented for the frequently encountered alkane/cycloalkane separations in petrochemical industry. Exhaustive experimental data are first collected to extend the UNIFAC-IL model for this system, where the proximity effect in alkanes and cycloalkanes is considered specifically by defining distinct groups. The thermodynamic performances of a large number of ILs for 4 different alkane/cycloalkane systems are then compared to select a representative example of such separations. By applying n-heptane/methylcyclohexane extractive distillation as a case study, the CAILD task is cast as a mixed-integer nonlinear programming (MINLP) problem based on the obtained task-specific UNIFAC-IL model and two semi-empirical models for IL physical properties. The top 5 IL candidates determined by solving the MINLP problem are subsequently introduced into Aspen Plus for process simulation and economic analysis, which finally identify 1-hexadecyl-methylpiperidinium tricyanomethane ([C16MPip][C(CN)3]) as the best entrainer for this separation.

     

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