Translation of Batch to Continuous Flow in Photoredox Reactions

Tomohiro Yasukawa, Shū Kobayashi

Research output: Contribution to journalArticleOtherpeer-review

2 Citations (Scopus)

Abstract

The vast majority of chemical syntheses are carried out by either batch or flow methods (Figure 1). Batch methods are commonly used for fine chemical synthesis in fields such as active pharmaceutical ingredients (APIs), agrochemicals, and fragrances; in this approach, all reagents are charged into a reaction vessel where they react. In the flow method, materials are continuously introduced from one end into a hollow loop or column as reactors, and products are continuously eluted from the other end. The continuous-flow method has several advantages over the batch method in terms of efficiency, safety, and scalability, and is suitable for on-demand synthesis. Another advantage can be seen in photoredox catalysis, in which photon-harvesting molecules convert light energy into chemical energy. Photoredox catalysis is currently being studied very extensively because it is environmentally friendly and can be used to achieve unique reactions via high-energy intermediates. However, most of these processes have been developed as batch methods, which pose a problem for scale-up. This is because, as known by the Beer–Lambert law, when the volume of the reaction vessel is increased, insufficient light intensity may reach the interior of the reaction mass. Flow reactions, which utilize a narrow tubular space, can be used to overcome this problem. Despite the many advantages, research on the synthesis of fine chemicals by flow reactions has lagged far behind that of batch reactions, and a method to develop flow reactions more rapidly is desired. In this issue of ACS Central Science, MacMillan et al. describe an approach in which microscale high-throughput experimentation (HTE) is used to identify optimal reaction conditions that can be directly translated to flow systems.
Original languageEnglish
Pages (from-to)1099-1101
Number of pages3
JournalACS Central Science
Volume7
Issue number7
DOIs
Publication statusPublished - 28 Jul 2021
Externally publishedYes

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