Optimization of an improved single-column chromatographic process for the separation of enantiomers

This work addresses optimization of an improved single-column chromatographic (ISCC) process for the separation of guaifenesin enantiomers. Conventional feed injection and fraction collection systems have been replaced with customized components facilitating simultaneous separation and online monitoring with the ultimate objective of application of an optimizing controller. Injection volume, cycle time, desorbent flow rate, feed concentration, and three cut intervals are considered as decision variables. A multi-objective optimization technique based on genetic algorithm (GA) is adopted to achieve maximum productivity and minimum desorbent requirement in the region constrained by product specifications and hardware limitations. The optimization results along with the contribution of decision variables are discussed using Pareto fronts that identify non-dominated solutions. Optimization results of a similar simulated moving bed process have also been included to facilitate comparison with a continuous chromatographic process.

► Conceptual design of an improved single-column chromatographic (ISCC) separation process has been presented.
► The ISCC process has been optimized using a multi-objective evolutionary algorithm.
► Results show that the proposed fraction collection scheme and overlapped peaks can enhance productivity and decrease desorbent requirement.