Artificial intelligence in computational materials science

In this themed collection we aim to broadly review some of the critical, recent progress in the application of AI/ML to various aspects of computational materials science and materials science more broadly. In this collection spread across two issues, we have assembled a collection of articles from...

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Bibliographic Details
Published in:MRS bulletin 2022-09, Vol.47 (9), p.927-929
Main Authors: Kulik, Heather J., Tiwary, Pratyush
Format: Article
Language:English
Subjects:
Applied and Technical Physics
Artificial intelligence
Characterization and Evaluation of Materials
Chemistry and Materials Science
Collection
Crystal growth
Energy Materials
Materials Engineering
Materials Science
Nanotechnology
Nucleation
Physics
Review Article
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Summary:In this themed collection we aim to broadly review some of the critical, recent progress in the application of AI/ML to various aspects of computational materials science and materials science more broadly. In this collection spread across two issues, we have assembled a collection of articles from leaders in the broad domain of applying AI/ML, which we collectively refer to as ML, in computational materials science. Together these articles curate the critical, recent progress in the application of ML to various aspects of materials science. These include ML approaches for understanding and driving electron microscopy, designing energy materials and the discovery of principles and materials relevant to the design of materials for the future, studying crystal nucleation and growth, the use of ML to describe force fields governing material and molecular behavior, and other topics. Graphical abstract
ISSN:0883-7694
1938-1425
DOI:10.1557/s43577-022-00431-1