Systematic optimization and experimental validation of ternary simulated moving bed chromatography systems.

Area of Science:

• Chemical Engineering
• Separation Science
• Chromatography

Background:

• Simulated Moving Bed (SMB) chromatography is crucial for binary mixture separation, but multi-component mixture separation remains a significant challenge.
• Existing computational studies proposed strategies like JO and Generalized Full Cycle (GFC) for ternary separations, yet lacked experimental validation.

Purpose of the Study:

• To experimentally validate the performance of both the JO process and the proposed Generalized Full Cycle (GFC) SMB operating strategies.
• To achieve optimal operating conditions for enhanced productivity, purity, and recovery in multi-component SMB separations.

Main Methods:

• Experimental validation of JO and Generalized Full Cycle (GFC) simulated moving bed (SMB) systems.
• Implementation of a simultaneous optimization and model correction scheme.
• Determination of optimal operating conditions for productivity, purity, and recovery.

Main Results:

• Experimental validation confirmed the effectiveness of the Generalized Full Cycle (GFC) strategy over existing methods for multi-component SMB separation.
• The implemented optimization scheme successfully identified operating conditions that satisfy high productivity, purity, and recovery targets.
• Significant improvements in SMB process performance were demonstrated through experimental validation.

Conclusions:

• The Generalized Full Cycle (GFC) strategy provides a robust and experimentally validated approach for challenging multi-component SMB separations.
• This work bridges the gap between computational design and experimental implementation, offering practical guidelines for SMB process optimization.