A high-throughput exploration of magnetic materials by using structure predicting methods

被引:13
|
作者
Arapan, S. [1 ,2 ]
Nieves, P. [1 ,2 ]
Cuesta-Lopez, S. [1 ,2 ]
机构
[1] Univ Burgos, Int Res Ctr Crit Raw Mat & Adv Ind Technol, ICCRAM, Burgos 09001, Spain
[2] Univ Burgos, Adv Mat Nucl Technol & NanoBioTechnol Dept, Burgos 09001, Spain
关键词
PERMANENT-MAGNETS; MN; AL;
D O I
10.1063/1.5004979
中图分类号
O59 [应用物理学];
学科分类号
摘要
We study the capability of a structure predicting method based on genetic/evolutionary algorithm for a high-throughput exploration of magnetic materials. We use the USPEX and VASP codes to predict stable and generate low-energy meta-stable structures for a set of representative magnetic structures comprising intermetallic alloys, oxides, interstitial compounds, and systems containing rare-earths elements, and for both types of ferromagnetic and antiferromagnetic ordering. We have modified the interface between USPEX and VASP codes to improve the performance of structural optimization as well as to perform calculations in a high-throughput manner. We show that exploring the structure phase space with a structure predicting technique reveals large sets of low-energy metastable structures, which not only improve currently exiting databases, but also may provide understanding and solutions to stabilize and synthesize magnetic materials suitable for permanent magnet applications. (C) 2018 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license.
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页数:8
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