Data-driven Discovery in the Chemical Sciences

Big data, machine learning and artificial intelligence are becoming increasingly central in the chemical sciences. It is important to consider how data drives new discoveries in chemistry at present and how data-driven discovery may develop in the future.

This Faraday Discussion is an excellent format to record the in-depth, interdisciplinary discussions held between academic and industrial scientists from both molecular and materials fields. It offers new insights on how data-driven discovery advances chemical sciences and examines the ongoing role of data-driven discovery in these fields, in terms of both recent developments and future possibilities. In this volume, the topics covered are organised into the following themes:

Discovering chemical structure
Discovering structure-property correlations
Discovering trends in big data
Discovering synthesis targets