Batch reaction analysis examples

In general, the desired product of a reaction is rarely obtained as the sole product of a reaction. Reactions are often complicated and include competitive, successive, and reverse reactions.

In this example, we demonstrated the analysis of the behavior in the reaction using HPLC and React-IR^TM and calculated the reaction rate from the estimated elementary reactions using reaction analysis softwares. In addition, from different rates of each elementary reaction, we identified which reaction would proceed most easily. Based on these results, we set up the optimal addition method and reaction temperature, and maximized the yield of the target product.

During the optimization of the reaction conditions, a variety of factors such as temperature, types and volume of additives, solvents, and pH contribute to the reaction output. In the case of traditional method to optimize each influencing factor one-by-one, it requires a large number of experiments and may not even result in the absolute optimization of the reaction. Multivariate analysis is a statistical method used to analyze the correlation between complex variables based on data.

In this example, we demonstrated the degree to which each factor contributed to the formation of impurities by multivariate analysis and selected the optimal reaction conditions with a small number of experiments. We understand the important factors of the reaction by the multivariate analysis results, which helps build the design space of process.

In batch reactions, the agitation has a significant impact on the reaction output. Therefore, we evaluate reactions with flow analysis for which agitation may be effective in advance.

This example demonstrated the agitation impact to conduct the scale-up of a liquid-liquid phase reaction. In this liquid-liquid phase reaction, the movement of the substances between the phases is the factor limiting the rate in the reaction. If there is insufficient movement or miscibility, this may cause the unexpected results upon scale-up. We analyzed the fluid in the reactor that may be used upon scale-up and evaluated the validity of the assigned reactor in advance. In this case, we compared the difference between anchor and three-blade retreat impeller on the miscibility. The red and blue portions represent the organic and aqueous layers, respectively. The other colors represent the mixture of the organic and aqueous layers. It shows that using three-blade retreat impeller resulted in better miscibility, which could be used to predict the validity of the assigned reactor upon comparison to the laboratory performance.