Machine learning approaches for the prediction of materials properties
Author(s) -
Siwar Chibani,
FrançoisXavier Coudert
Publication year - 2020
Publication title -
apl materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.571
H-Index - 60
ISSN - 2166-532X
DOI - 10.1063/5.0018384
Subject(s) - workflow , field (mathematics) , computer science , materials science , data science , machine learning , artificial intelligence , management science , engineering , mathematics , database , pure mathematics
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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