(227d) Speedy Standing Wave Design and Splitting Strategies for the Separation of Mixtures with Three or More Components Using Simulated Moving Beds

Simulated Moving Beds (SMBs) consume orders of magnitude less solvent, require an order of magnitude less sorbent, and take up less space than batch chromatography operations. As a result, SMBs are economical for large-scale separations. Although SMBs have many advantages, they have not been widely used for large-scale production. One key barrier is the complexity of the design and optimization of SMBs. A four-zone SMB for a separation of four components with linear isotherms has 31 variables, which include 15 material properties and 16 design parameters (four yields, five operating parameters, and seven equipment parameters).

Furthermore, for a mixture of three or more components, more than one SMB may be needed in tandem to recover one or more target products. If there is only one target product in the feed and it happens to be the most (or least) retained component, then only one SMB is needed to recover the pure product. If the target product is an intermediately retained species, then at least two SMBs in tandem are required to recover the pure product. When the target component is not the most (or the least) retained species in a mixture of four or more components, there can be many splitting options (or choice of which components are recovered in which product streams). There are no general rules for finding the most economical splitting strategy in the literature.

The Standing Wave concept was used for size-exclusion systems with three components to develop analytical expressions for solvent consumption and sorbent productivity as a function of dimensionless groups. The resulting Speedy Standing Wave Design (SSWD) equations have been incorporated into a computer program to quickly find the optimal design parameters for maximum productivity, minimum solvent consumption, or minimum cost.

In this work, the SSWD is extended to systems with three or more components with linear adsorption isotherms. The SSWD equations can be simplified for diffusion-controlled systems. The computer program based on the SSWD equations can quickly find the design and operating parameters which can achieve the desired product yields and are optimal for productivity, solvent consumption, or separation costs. In addition, SSWD program can find the optimal SMB designs for each of the many possible splitting options in order to compare the performance of each splitting option. The program can also evaluate different adsorbents for the various SMBs in the splitting cascade.

The number of possible splitting options (SO) is related to the number of components (n) by the following equation: SO = (n²-1)(n²+2n)/24. To recover an intermediate product, the first split should be between the target solute and the adjacent solute with the largest difference in retention factor. In other words, the easiest separation should be performed first. Solvent consumption can be significantly reduced by allowing certain components to distribute between the product ports. For the same yield, purity, and productivity, choosing the correct splitting strategy can save solvent and increase product concentration by an order of magnitude.