Standing-Wave Design of a Simulated Moving Bed under a Pressure Limit for Enantioseparation of Phenylpropanolamine

Abstract

An improved standing-wave design method is developed for nonlinear simulated moving bed (SMB) systems with significant mass-transfer effects and an operating pressure limit. The design method was verified with rate model simulations and then tested for enantioseparation of phenylpropanolamine. High purity (>99%) and high yield (>99%) were achieved experimentally using a SMB with a pressure limit of 350 psi. The verified design method was used to find the optimal column length that gives the maximum throughput per bed volume. For a given particle size and a pressure limit, the optimal column length falls on the boundary between the masstransfer-limiting region and the pressure-limiting region. If a characteristic dispersion velocity is more than 0.2% of an interstitial velocity, mass-transfer effects must be considered in the design in order to guarantee 99% purity and yield.

Simulated moving bed multiobjective optimization using standing wave design and genetic algorithm

“…The velocity differences that are needed to focus the waves, and to maintain certain desired product purity and yield, have been derived and verified experimentally for nonideal systems in several previous studies. 25,26,28,29 …”

“…The maximum feed velocity is a function of the phase ratio, the retention factors, the lumped mass-transfer coefficients, the lengths of Zones II and III, and the yield. 26 In practice, an SMB system has a maximum pressure limit, which can also limit the feed velocity. Lee et al 26 incorporated a pressure limit into the SWD.…”

“…26 In practice, an SMB system has a maximum pressure limit, which can also limit the feed velocity. Lee et al 26 incorporated a pressure limit into the SWD. The maximum pressure drop in a given system depends on zone configuration and pump configuration.…”

“…SWD was first developed by Ma and Wang 23 for linear isotherm systems and further developed by Mallmann et al, 24 Xie et al, 25 and Lee et al 26 for nonlinear isotherm systems. SWD can guarantee high product purity and high yield even in the systems with significant mass-transfer resistances and axial dispersion.…”

“…SWD can guarantee high product purity and high yield even in the systems with significant mass-transfer resistances and axial dispersion. 23,25,26 SWD involves solving only algebraic equations, instead of solving ordinary differential equations or partial differential equations as required in the previous optimization studies using process simulations. Therefore, multiobjective optimization using SWD significantly increases the computation speed.…”