Microreactor system for reaction development and online optimization of chemical processes

摘要

Developing the optimal conditions for chemical reactions that are common in fine chemical and pharmaceutics is a difficult and expensive task. Because syntheses in these fields have multiple reaction pathways, a significant number of experiments are required to determine the conditions that maximize the yield of the desired product. With few exceptions, these experiments have been performed in flask reactors. The goal of this thesis research was to improve the efficiency and the accuracy of these reaction optimization investigations through the use of an automated microreactor system. Previous studies have illustrated the benefits of silicon microreactors for the study of chemical reactions. Such advantages include the small reactor volume and the continuous flow operations that enable microreactors to achieve a high throughput rate of experiments while using minute amounts of expensive material. Heat and mass transfer rates in microreactors are orders of magnitude larger than those in traditional laboratory equipment, thus rendering microreactors ideal tools for accurate reaction optimization and kinetic investigations. Moreover, the integration of chemical and physical sensors with microreactors permits accurate monitoring of the reaction progress. Combining these measurements with appropriate feedback algorithms offers a means to automate experiments and to perform real-time optimization and kinetic modeling of chemical reactions. Several automated microreactor systems were developed in this thesis research to improve reaction development. One such system was used in the multidimensional screening investigation of densely functionalized heterocycles. As demonstrated in this example, the use of an automated microreactor system greatly improved the speed and efficiency involved in reaction library development. Incorporating a feedback algorithm into the system operations provided a method for rapid reaction optimization. With throughputs as high as one experiment performed and analyzed per 10 minutes, rapid multi-variable reaction optimization was demonstrated for several chemistries. It was also possible to quickly and accurately extract the kinetics of a reaction by incorporating model-based optimization approaches. The results from these optimization studies were used to scale up reaction production by factors as large as 500 in a mesoflow reaction system. Future extensions for automated microflow systems were identified, and the technology developed in this thesis research was used to optimize a two-step synthesis and to more efficiently study reactions that produce solid by-products.