PHI-PLOT OPTIMIZATION STUDIES OF SOLVENT GRADIENT SIMULATED MOVING BED (SG-SMB) SEPARATION OF THE AMINO ACIDS TRYPTOPHAN AND TYROSINE

Abstract

The phi-plot optimization approach has been effectively used as a search routine to determine the best operational settings for solvent-gradient simulated moving bed process (SG-SMB) separation of various molecular combinations, such as amino acids. Modulating the solvent strength (SG-SMB) improves the performance of the simulated moving bed process-SMB, resulting in a significant increase in purities and productivity, as well as a reduction in solvent consumption. The amino acids tryptophan and tyrosine were separated using the phi-plot optimization method, which has never been investigated before in the context of SG-SMB process separation. The mass transfer kinetic parameters were determined through the chromatographic dynamic data and incorporated into the SG-SMB simulator for the validation of the optimization conditions by the Phi-plot method. A series of optimization studies were carried out varying the solvent concentration and the process flow rates in the context of triangle theory. The dynamic stepwise SG-SMB simulator was used to evaluate the ideal operational conditions for separation using the phi-plot optimization approach. For the conditions studied, the new phi-plot optimization approach was able to determine the optimal operational settings for producing high-purity separations in the extract and raffinate, which was validated by the simulator. The optimization results of the studied conditions were plotted in the triangle theory separation regions which confirms the optimization technique as a viable search routine for such complex task of determination of the best operational conditions of SG-SMB.