A Paradigm Shift: From Batch Processing to Flow Chemistry

Abstract

Customisable flow chemistry reactors are becoming more affordable and accessible to wider research community. Coupled with rapidly advancing machine learning (ML) optimisation algorithms, time consuming research activities like catalyst discovery, reaction screening and optimisation can now be achievable quicker in flow, placing us in an interesting crossroad: should we start thinking about flow integration earlier in the research phase? In this perspective, parallels and differences between batch and flow heterogeneous catalytic reaction optimisations will be discussed with practical examples. Challenges in flow and batch processing are compared, combined with fresh perspectives of how reaction conditions can be adjusted more flexibly in multi-pass flow setting. Finally, recent progress of integrating computational techniques into flow process optimisation of contemporary “chemical looping” and paired reactions for more sustainable chemical productions will also be discussed.