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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/16009

Title: Machine learning reveals orbital interaction in materials
Authors: Pham, Tien Lam
Kino, Hiori
Terakura, Kiyoyuki
Miyake, Takashi
Tsuda, Koji
Takigawa, Ichigaku
Dam, Hieu Chi
Keywords: Materials Informatics
Machine learning
Data mining
Issue Date: 2017-10-26
Publisher: Taylor and Francis
Magazine name: Science and Technology of Advanced Materials
Volume: 18
Number: 1
Start page: 756
End page: 765
DOI: 10.1080/14686996.2017.1378060
Abstract: We propose a novel representation of materials named an ‘orbital-field matrix (OFM)’, which is based on the distribution of valence shell electrons. We demonstrate that this new representationcan be highly useful in mining material data. Experimental investigation shows that the formationenergies of crystalline materials, atomization energies of molecular materials, and local magneticmoments of the constituent atoms in bimetal alloys of a lanthanide metal and transition-metal can be predicted with high accuracy using the OFM. Knowledge regarding the role of the coordinationnumbers of the transition-metal and lanthanide elements in determining the local magnetic moments of the transition-metal sites can be acquired directly from decision tree regressionanalyses using the OFM.
Rights: Tien Lam Pham, Hiori Kino, Kiyoyuki Terakura, Takashi Miyake, Koji Tsuda, Ichigaku Takigawa, and Hieu Chi Dam, Science and Technology of Advanced Materials, 18(1), 2017, 756-765. DOI:10.1080/14686996.2017.1378060. c 2017 The Author(s). Published by National Institute for Materials Science in partnership with Taylor & Francis. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
URI: http://hdl.handle.net/10119/16009
Material Type: publisher
Appears in Collections:a10-1. 雑誌掲載論文 (Journal Articles)

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