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Comparison of various ternary simulated moving bed separation schemes by multi-objective optimization.
Gaurav Agrawal1, Yoshiaki Kawajiri
1School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
This study optimizes simulated moving bed (SMB) chromatography for multi-component mixtures, enhancing productivity and purity. A generalized full cycle (GFC) formulation identifies superior ternary separation strategies.
Area of Science:
- Chemical Engineering
- Separation Science
- Chromatography
Background:
- Simulated Moving Bed (SMB) chromatography has seen numerous modifications for binary mixtures.
- Separating multi-component mixtures with SMB remains a significant challenge.
- SMB system performance is highly sensitive to operating conditions.
Purpose of the Study:
- To address the challenge of multi-component separation in SMB chromatography.
- To develop a multi-objective optimization framework maximizing both productivity and purity.
- To identify optimal operating schemes for ternary SMB systems.
Main Methods:
- Formulation of a multi-objective optimization problem.
- Comparison of optimized isocratic ternary SMB operating schemes.
- Proposal of a generalized full cycle (GFC) formulation using superstructure.
- Evaluation of various operating schemes within the GFC framework.
Main Results:
- Optimized isocratic ternary SMB schemes were compared for productivity and desorbent-to-feed ratio.
- The generalized full cycle (GFC) formulation encompasses existing literature schemes.
- Demonstration of the GFC approach's potential in selecting the best ternary separation strategy.
Conclusions:
- The developed multi-objective optimization effectively balances productivity and purity for multi-component SMB separation.
- The generalized full cycle (GFC) formulation provides a unified approach to evaluate and discover optimal SMB operating strategies.
- This work offers a pathway to significantly improve the efficiency of complex separations using SMB chromatography.
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