Accelerated Materials Discovery : How to Use Artificial Intelligence to Speed Up Development / edited by Phil De Luna.

Format:

Book

Contributor:

De Luna, Phil, editor.

Series:

De Gruyter STEM.

De Gruyter STEM

Language:

English

Subjects (All):

Materials.

Artificial intelligence--Engineering applications.

Artificial intelligence.

Physical Description:

1 online resource (205 pages). : illustrations.

Other Title:

Accelerated Materials Discovery

Place of Publication:

Berlin : De Gruyter, 2022.

Summary:

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). * ighlights artificial intelligence and robotics to speed up the discovery of advanced materials * Describes machine learning algorithms, self-driving labs, AI in catalysis and spectroscopy, and industrial use cases.

Notes:

Description based on: online resource; title from PDF information screen (De Gruyter, viewed November 25, 2022).

Includes index.

ISBN:

9783110733259

3110733250