226 / 2023-04-17 11:09:59

Crystal structure prediction method MAGUS and its applications

First-principles calculations,materials design,planetary interior,superionic,high temperature and high pressure

高压物理与材料科学 > 功能材料

ABSTRACT

In this talk, I will introduce the machine learning and graph theory assisted crystal structure prediction method (MAGUS) [1] developed in my group. In addition, I will show some of our recent progress in the applications of this method to predict new compounds, including planetary minerals [2-6] and functional materials, including superhard, high energy density, and superconducting materials [7-8], etc.



MAGUS code registration：

https://www.wjx.top/vm/m5eWS0X.aspx





REFERENCE

1. Kang Xia et al., “A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure search”, Sci. Bull. 63, 817 (2018).


2. Shuning Pan et al., “Magnesium oxide-water compounds at megabar pressure and implications on planetary interiors”, Nat. Commun. 14, 1165 (2023).


3. Hao Gao et al., “Superionic Silica-Water and Silica-Hydrogen Compounds in the Deep Interiors of Uranus and Neptune”, Phys. Rev. Lett. 128, 035702 (2022).


4. Cong Liu et al., “Multiple superionic states in helium-water compounds”, Nature Physics 15, 1065 (2019).


5. Cong Liu et al., “Plastic and Superionic Helium Ammonia Compounds under High Pressure and High Temperature”, Phys. Rev. X 10, 021007 (2020).


6. Cong Liu et al., “Mixed coordination silica at megabar pressure”, Phys. Rev. Lett. 126, 035701 (2021).


7. Nilesh P. Salke et al., “Tungsten hexanitride with single-bonded armchair-like hexazine structure at high pressure”, Phys. Rev. Lett. 126, 065702 (2021).


8. Xiaomeng Wang et al., “Pressure Stabilized Lithium-Aluminum Compounds with Both Superconducting and Superionic Behaviors”, Phys. Rev. Lett. 129, 246403 (2022).