Issue 17, 2020

Machine learning the ropes: principles, applications and directions in synthetic chemistry

Abstract

Machine learning (ML) has emerged as a general, problem-solving paradigm with many applications in computer vision, natural language processing, digital safety, or medicine. By recognizing complex patterns in data, ML bears the potential to modernise the way how many chemical challenges are approached. In this review, an introduction to ML is given from the perspective of synthetic chemistry: starting from the fundamentals regarding algorithms and best-practice workflows, the review covers different applications of machine learning in synthesis planning, property prediction, molecular design, and reactivity prediction. In particular, different approaches of representing and utilizing organic molecules will be discussed – providing synthetic chemists both with the understanding and the tools required to apply machine learning in the context of their research, and pointers for further studying.

Graphical abstract: Machine learning the ropes: principles, applications and directions in synthetic chemistry

Supplementary files

Article information

Article type
Tutorial Review
Submitted
31 Mar 2020
First published
16 Jul 2020

Chem. Soc. Rev., 2020,49, 6154-6168

Machine learning the ropes: principles, applications and directions in synthetic chemistry

F. Strieth-Kalthoff, F. Sandfort, M. H. S. Segler and F. Glorius, Chem. Soc. Rev., 2020, 49, 6154 DOI: 10.1039/C9CS00786E

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements