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Multiobjective optimization of simulated moving bed and Varicol processes using a genetic algorithm.

Ziyang Zhang1, Marco Mazzotti, Massimo Morbidelli

  • 1Swiss Federail Institute of Technology Zürich, Laboratorium für Technische Chemie/LTC, ETH-Hönggerberg/HCI, CH-8093 Zürich, Switzerland.

Journal of Chromatography. A
|March 19, 2003
PubMed
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Optimizing preparative chromatography involves balancing packing material size, column number, and feed concentration. This study reveals how these factors impact simulated moving bed (SMB) and Varicol process economics for chiral separations.

Area of Science:

  • Chemical Engineering
  • Separation Science
  • Chromatography

Background:

  • Preparative chromatography is crucial for purifying valuable compounds.
  • Process economics are significantly influenced by packing material size, column count, and feed concentration.
  • These parameters affect critical performance metrics like column pressure drop, efficiency, and thermodynamics.

Purpose of the Study:

  • To investigate the impact of packing material size, total columns, and feed concentration on simulated moving bed (SMB) and Varicol processes.
  • To optimize and compare the performance of SMB and Varicol for a specific chiral separation.
  • To clarify the roles of these key parameters within the framework of equilibrium theory.

Main Methods:

  • Utilized an equilibrium stage model for process simulation.

Related Experiment Videos

  • Employed a multi-objective optimization technique based on a genetic algorithm.
  • Analyzed Pareto sets to understand trade-offs between purity and productivity.

    • Main Results:

    • Identified optimal parameter ranges for both SMB and Varicol processes.
    • Demonstrated the ability to simultaneously maximize extract purity and unit productivity.
    • Clarified the influence of packing material size, column number, and feed concentration on process performance.

    Conclusions:

    • The study provides a framework for optimizing preparative chromatographic separations.
    • Simulated moving bed and Varicol processes can be effectively compared under optimized conditions.
    • Equilibrium theory effectively explains the observed parameter influences on separation performance.