Nanyang Technological University, School of Chemical and Biomedical Engineering, 62 Nanyang Drive, Singapore 637459, Singapore.
J Chromatogr A. 2012 Mar 30;1231:22-30. doi: 10.1016/j.chroma.2012.01.057. Epub 2012 Jan 28.
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.
这项工作针对的是优化改进的单柱色谱（ISCC）工艺，以分离愈创甘油醚对映异构体。已用定制组件替代了传统的进料注入和馏分收集系统，这有利于同时进行分离和在线监测，最终目标是应用优化控制器。注射体积、循环时间、洗脱剂流速、进料浓度和三个切割间隔被视为决策变量。采用基于遗传算法（GA）的多目标优化技术，在产品规格和硬件限制所约束的区域内实现最大生产力和最小洗脱剂需求。使用 Pareto 前沿图讨论了优化结果以及决策变量的贡献，该图确定了非支配解。还包括了类似模拟移动床工艺的优化结果，以方便与连续色谱工艺进行比较。
