Boosting Material Modeling Using Game Tree Search

Abstract

We demonstrate a heuristic optimization algorithm based on the game tree search for multi-component 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 anti-site disorder and show that [Fe${}_{0.9}$Co${}_{0.1}$]${}_2$Cr${}_{0.95}$Mn${}_{0.05}$Si${}_{0.3}$Ge${}_{0.7}$ has the potential to be a high spin polarized material with robustness against anti-site disorder.

arXiv comment5 pages, 6 figures

References in corpus (6)

• Slater-Pauling Behavior of the Half-Ferromagnetic Full-Heusler Alloys
• Towards New Half-Metallic Systems: Zinc-Blende Compounds of Transition Elements with N, P, As, Sb, S, Se, and Te
• Spin-polarization and electronic properties of half-metallic Heusler alloys calculated from first-principles
• Appearance of Half-Metallicity in the Quaternary Heusler Alloys
• Effect of doping and disorder on the half-metallicity of full Heusler alloy
• Thermodynamics of the Heusler alloy Co_2-xMn_1+xSi: a combined density functional theory and cluster expansion study

Cited by in corpus (1)

• Efficient Construction Method for Phase Diagrams Using Uncertainty Sampling