Design, development, and modeling of a continuous simulated moving-bed ion-exclusion process for the separation of acid and sugar
Current concern for the environment and anticipated future shortages of fossil fuels has inspired research into the use of cellulosic waste materials as fuel sources. One option is to hydrolyze the cellulosic materials into sugar that can be fermented into fuel grade alcohol. This research demonstrates the efficient separation of the sugar from the acid used for hydrolysis. A simulated moving bed ion exclusion chromatography system was constructed for the continuous separation of the components in an aqueous feed solution of sucrose and sulfuric acid. A system of 18 columns was arrayed about a central manifold system. Each column was packed with approximately 820 mL of porous cationic exchange resin. The system was designed for the flexibility to use fluid recycle loops and unrestricted placement of all inlet and outlet streams. Monitoring and control functions were performed using a Camile 2000 process controller integrated with a custom-built control computer. The aqueous feed solution, usually containing 10 wt.% sucrose and 10 wt.% sulfuric acid, was generally introduced into the system at a rate of roughly 2 L/hr. Approximately 4 L/hr of water was used to elute materials through the separation system. The unoptimized separation system allowed greater than 95% recovery of the feed sucrose in an exit stream containing 8.8 wt.% sucrose and 98% recovery of the feed acid in a second exit stream containing 5 wt.% acid. The system has been successfully operated with 2 of the 7 resins evaluated for use in the system using 2 k factorial experimental design in fixed-bed tests. The screening studies including model equations for the ion exclusion separation process are reported here. A numerical simulation model of the process has been developed and tested using experimental data from the system arrayed with both 18 and 9 columns. The model allows study of the continuous separation process and provides a low-cost test bed for optimization studies. The numerical simulation model was used in conjunction with statistical experimental design techniques to probe the optimum operating conditions, including the selection of the simulated flow rate and the number of columns needed in each zone.