报告：New materials and new states under high pressure predicted from first-principles
报告人： 孙建 （南京大学，杰青）
In this talk, I will introduce the methods developed in my group, including a machine learning accelerated crystal structure prediction method , and a method determining the dimensionality and multiplicity of crystal nets using quotient graph . In addition, I will show some of our recent progresseson the applications of these methods combining with first-principles calculations, for instance, the predictions on newcompounds [3-4] and their exotic new states under planetary conditions (superionic state, plastic state, and coexistence) [5-7], as well as the superionic-like cooperative diffusion in an elemental system , etc.
1. Kang Xia et al., “A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure search”, Sci. Bull.63, 817 (2018).
2. Hao Gao, Junjie Wang, Zhaopeng Guo, Jian Sun, “Determining dimensionalities and multiplicities of crystal nets” npj Comput. Mater. 6, 143 (2020).
3. Cong Liu et al., “Mixed coordination silica at megabar pressure”, Phys. Rev. Lett. 126, 035701 (2021).
4. Nilesh P. Salke et al., “Tungsten hexanitride with single-bonded armchair-like hexazine structure at high pressure”, Phys. Rev. Lett. 126, 065702 (2021).
5. Cong Liu et al., “Multiple superionic states in helium-water compounds”, Nature Physics 15, 1065 (2019).
6. Cong Liu et al., “Plastic and Superionic Helium Ammonia Compounds under High Pressure and High Temperature”, Phys. Rev. X 10, 021007 (2020).
7. Hao Gao et al., “Coexistence of plastic and partially diffusive phases in a helium-methane compound”, Natl. Sci. Rev. 7, 1540 (2020).
8. Y. Wang et al., “Electronically driven 1D cooperative diffusion in a simple cubic crystal”, Phys. Rev. X 11, 011006 (2021).