Machine learning approaches for the prediction of materials properties

We give here a brief overview of the use of machine learning (ML) in our field, for chemists and materials scientists with no experience with these techniques. We illustrate the workflow of ML for computational studies of materials, with a specific interest in the prediction of materials properties....

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Published in:APL materials 2020-08, Vol.8 (8), p.080701-080701-10
Main Authors: Chibani, Siwar, Coudert, François-Xavier
Format: Article
Language:English
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Chemical Sciences
Material chemistry
or physical chemistry
Theoretical and
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description We give here a brief overview of the use of machine learning (ML) in our field, for chemists and materials scientists with no experience with these techniques. We illustrate the workflow of ML for computational studies of materials, with a specific interest in the prediction of materials properties. We present concisely the fundamental ideas of ML, and for each stage of the workflow, we give examples of the possibilities and questions to be considered in implementing ML-based modeling.
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subjects Chemical Sciences
Material chemistry
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Theoretical and
title Machine learning approaches for the prediction of materials properties
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