Boosting material modeling using game tree search

被引：14
|
作者：
Sawada, Ryohto [1 ]
Iwasaki, Yuma [1 ,2 ]
Ishida, Masahiko [1 ]
机构：
[1] NEC Corp Ltd, IoT Devices Res Labs, Tsukuba, Ibaraki 3058501, Japan
[2] JST, PRESTO, Saitama 3320012, Japan
来源：
PHYSICAL REVIEW MATERIALS | 2018年 / 2卷 / 10期
关键词：
KKR-CPA METHOD; GENETIC ALGORITHM; HEUSLER ALLOYS; HALF-METALLICITY; OPTIMIZATION;
D O I：
10.1103/PhysRevMaterials.2.103802
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
We demonstrate a heuristic optimization algorithm based on the game tree search for multicomponent materials design. The algorithm searches for the largest spin polarization of seven-component Heusler alloys. The algorithm can find the peaks quickly and is more robust against local optima than Bayesian optimization approaches using the expected improvement or upper confidence bound approaches. We also investigate Heusler alloys, including antisite disorder, and we show that [Fe0.9Co0.1](2)Cr0.95Mn0.05Si0.3Ge0.7 has the potential to be a high-spin-polarized material with robustness against antisite disorder.
引用
收藏
页数：5
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