Development of System for Selecting Optimal Combination of Zeolite and Solvent for Simulated Moving Bed Processes

Abstract

A prediction system for the quantity of an adsorbed organic compound on zeolite has been developed. The regression model useful for a various combinations of zeolite and solvent has readily been developed using genetic algorithm partial least squares (GAPLS). In the models, the molecular descriptor of the organic compound is used as an explanatory variable and the partition coefficient is used as an objective variable. As a result, the system can provide accurate predictions for almost of all combinations. Additionally, with the GA-PLS method, we applied the system to selecting the optimal combination of zeolite and solvent for simulated moving bed (SMB) processes. The validity of the system was evaluated for separation of 2-adamantanone and 2-adamantanol as a representative case. The combinations selected by the system were almost the same as those selected by experiment. This system is intended to shorten the time for selecting the optimal zeolite/solvent combination and to ensure good selection accuracy for developing SMB methods.