Flow chemistry has unlocked a world of possibilities for the synthetic community, but the idea
that it is a mysterious “black box” needs to go. In this review, we show that several of the …

Abstract Machine learning (ML) promises to tackle the grand challenges in chemistry and
speed up the generation, improvement and/or ordering of research hypotheses. Despite the …

Reaction optimization is fundamental to synthetic chemistry, from optimizing the yield of
industrial processes to selecting conditions for the preparation of medicinal candidates …

General conditions for organic reactions are important but rare, and efforts to identify them
usually consider only narrow regions of chemical space. Discovering more general reaction …

Solutions to many of the world's problems depend upon materials research and
development. However, advanced materials can take decades to discover and decades …

The field of predictive chemistry relates to the development of models able to describe how
molecules interact and react. It encompasses the long-standing task of computer-aided …

The molecules of today—the medicines that cure diseases, the agrochemicals that protect
our crops, the materials that make life convenient—are becoming increasingly sophisticated …

High-throughput experimentation (HTE) is an increasingly important tool in reaction
discovery. While the hardware for running HTE in the chemical laboratory has evolved …

Modern chemistry is the backbone of our society, but it is also a major contributor to global
environmental pollution and the ongoing climate crisis. The transition toward a sustainable …

The explosion in the use of machine learning for automated chemical reaction optimization
is gathering pace. However, the lack of a standard architecture that connects the concept of …