Effect of mobile phase composition on the SMB processes efficiency: Stochastic optimization of isocratic and gradient operation - Ziomek, Grzegorz; Kaspereit, Malte; Jeżowski, Jacek; Seidel-Morgenstern, Andreas; Antos, Dorota (Journal of Chromatography A, 2005)
The solvent composition was adjusted in a theoretical study in order to maximize the efficiency of a simulated moving bed (SMB) process. The isocratic realization of the process as well as the solvent gradient mode were considered. The solvent composition and the flow rates were used as decision variables in a random search optimization algorithm known to be a reliable tool for nonlinear programming problems. The results of the optimization indicate that the optimal composition of the mobile phase depends strongly on the feed concentration. The asymmetry of the internal concentration profiles, which has a negative effect on the separation efficiency, can be partly damped by an increase of the solvent strength. In the cases studied the optimal solvent strength determined for concentrated feed streams is higher than that for diluted ones. Moreover, the optimum is strongly influenced by the value of the selectivity factor and its dependency on the mobile phase composition. Different results were obtained for cases, in which the separation factor increases with increasing the modifier concentration, than for cases, in which the separation factor decreases with increasing the modifier concentration. A similar analysis was performed for a solvent gradient SMB process, in which different solvents are used at the two inlet ports: a weak solvent in the feed stream and a strong solvent in the desorbent stream. Again the optimal mobile phase composition was strongly affected by the type of the isotherms and their non-linearity. The potential of a gradient SMB process in terms of increasing the productivity and reducing the eluent consumption is exemplified. © 2005 Elsevier B.V. All rights reserved.
Keywords: Gradient elution; Simulated moving bed chromatography; Stochastic optimization