Accelerated Materials Discovery: How to Use Artificial Intelligence to Speed Up Development

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Typical timelines to go from discovery to impact in the advanced materials sector are between 10 to 30 years. Advances in robotics and artificial intelligence are poised to accelerate the discovery and development of new materials dramatically. This book is a primer for any materials scientist looking to future-proof their careers and get ahead of the disruption that artificial intelligence and robotic automation is just starting to unleash. It is meant to be an overview of how we can use these disruptive technologies to augment and supercharge our abilities to discover new materials that will solve world's biggest challenges. Written by world leading experts on accelerated materials discovery from academia (UC Berkeley, Caltech, UBC, Cornell, etc.), industry (Toyota Research Institute, Citrine Informatics) and national labs (National Research Council of Canada, Lawrence Berkeley National Labs).

Author(s): Philip De Luna
Publisher: De Gruyter
Year: 2022

Language: English
Pages: 215
City: Berlin

Preface
Contents
List of contributors
1 An overview of accelerated materials discovery
2 Artificial intelligence for catalysis
3 Artificial intelligence for materials spectroscopy
4 Flexible automation for self-driving laboratories
5 Algorithms for materials discovery
6 Industrial materials informatics
About the editor
Index