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• An overview of the elements of continuous flow processes. • Synopsis of recent advancements in green continuous manufacturing strategies. • Synopsis of recent advancements in green reaction screening, process development, and optimization strategies. • Synopsis of future opportunities in green continuous flow processes. Recently, focus has turned towards increasing chemical process safety and sustainability for fundamental and applied research as well as manufacturing of pharmaceuticals and specialty chemicals. Flow chemistry techniques have attracted significant interest as a way to implement and improve chemical processes in order to satisfy the growing demand for chemical sustainability. In this article, we discuss emerging flow chemistry technologies with applications in green manufacturing of high-value chemicals and efficient screening of chemical reaction space. Continuous manufacturing techniques are increasingly being utilized to reduce the amount of material and energy utilized in a process while incorporating real-time analysis, control, and enhanced process safety. Beyond continuous production, flow screening techniques can rapidly search a multi-dimensional reaction space to improve process design, performance, and efficiency. Furthermore, time-efficient and material-efficient (green) flow screening platforms can be utilized to develop the next generation of process development technologies including predictive reaction models and process scale-up strategies. [ABSTRACT FROM AUTHOR]

Recent advances in machine learning (ML) and artificial intelligence have provided an exciting opportunity to computerize the fundamental and applied studies of complex reaction systems via self-driving laboratories. Autonomous robotic experimentation can enable time-, material-, and resource-efficient exploration and/or optimization of high-dimensional space reaction systems. Furthermore, interpretation of the ML models trained on the experimental data can unveil the underlying reaction mechanisms. In this article, we discuss different elements of a self-driving lab, and present recent efforts in autonomous reaction modeling and optimization. Further development and adoption of ML-guided closed-loop experimentation strategies can realize the full potential of autonomous chemical science and engineering to accelerate the discovery and development of advanced materials and molecules. • An overview of the elements of self-driving laboratories. • Recent advancements in autonomous chemical science and engineering. • Recent progress in closed-loop autonomous reaction modeling and optimization. • Future opportunities in surrogate model-based reaction exploration. [ABSTRACT FROM AUTHOR]