Prediction of Large Magnetic Moment Materials With Graph Neural Networks and Random Forests. (arXiv:2111.14712v3 [cond-mat.mtrl-sci] UPDATED)

Magnetic materials are crucial components of many technologies that could
drive the ecological transition, including electric motors, wind turbine
generators and magnetic refrigeration systems. Discovering materials with large
magnetic moments is therefore an increasing priority. Here, using
state-of-the-art machine learning methods, we scan the Inorganic Crystal
Structure Database (ICSD) of hundreds of thousands of existing materials to
find those that are ferromagnetic and have large magnetic moments. Crystal
graph convolutional neural networks (CGCNN), materials graph network (MEGNet)
and random forests …

arxiv graph graph neural networks materials networks neural networks prediction random random forests