A Universal 3D Voxel Descriptor for Solid-State Material Informatics with Deep Convolutional Neural Networks

A Universal 3D Voxel Descriptor for Solid-State Material Informatics with Deep Convolutional Neural Networks

Abstract Material informatics (MI) is a promising approach to liberate us from the time-consuming Edisonian (trial and error) process for material discoveries, driven by machine-learning algorithms. Several descriptors, which are encoded material features to feed computers, were proposed in the last...

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Autores principales: Seiji Kajita, Nobuko Ohba, Ryosuke Jinnouchi, Ryoji Asahi
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2017
Materias:
Medicine
R
Science
Q
Acceso en línea:https://doaj.org/article/08e609fd8d164525ba0be3498a88455a
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