New states under high pressure and high temperature from first-principles
Invited
Abstract
ABSTRACT
In this talk, I will briefly introduce the methods developed in my group, including a machine learning accelerated crystal structure prediction method [1], a machine learning force field using descriptor optimization [2], and a method determining the dimensionality and multiplicity of crystal nets using quotient graph [3]. In addition, I will show some of our recent progress on the applications of these methods, for instance, the predictions on the compounds and their new states under planetary conditions (superionic state, plastic state, and coexistence) [4-6], as well as the superionic-like cooperative diffusion in an elemental system [7].
REFERENCE
1. Kang Xia, Hao Gao, Cong Liu, Jianan Yuan, Jian Sun*, Hui-Tian Wang*, Dingyu Xing, "A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure search", Sci. Bull. 63, 817 (2018).
2. Hao Gao, Junjie Wang, and Jian Sun*, "Improve the performance of machine-learning potentials by optimizing descriptors", J. Chem. Phys. 150, 244110 (2019).
3. Hao Gao, Junjie Wang, Zhaopeng Guo, Jian Sun*, "Determining dimensionalities and multiplicities of crystal nets" npj Comput. Mater. 6, 143 (2020).
4. Cong Liu, Hao Gao, Yong Wang, Richard J. Needs, Chris J. Pickard, Jian Sun*, Hui-Tian Wang*, Dingyu Xing, "Multiple superionic states in helium-water compounds", Nature Physics 15, 1065 (2019).
5. Cong Liu, Hao Gao, Andreas Hermann, Yong Wang, Maosheng Miao, Chris J. Pickard, Richard J. Needs, Hui-Tian Wang, Dingyu Xing, and Jian Sun*, "Plastic and Superionic Helium Ammonia Compounds under High Pressure and High Temperature", Phys. Rev. X 10, 021007 (2020).
6. Hao Gao, Cong Liu, Andreas Hermann, Richard J. Needs, Chris J. Pickard, Hui-Tian Wang, Dingyu Xing, and Jian Sun*, "Coexistence of plastic and partially diffusive phases in a helium-methane compound", Natl. Sci. Rev. 7, 1540 (2020).
7. Y. Wang et al., "Electronically driven 1D cooperative diffusion in a simple cubic crystal", (submitted).
In this talk, I will briefly introduce the methods developed in my group, including a machine learning accelerated crystal structure prediction method [1], a machine learning force field using descriptor optimization [2], and a method determining the dimensionality and multiplicity of crystal nets using quotient graph [3]. In addition, I will show some of our recent progress on the applications of these methods, for instance, the predictions on the compounds and their new states under planetary conditions (superionic state, plastic state, and coexistence) [4-6], as well as the superionic-like cooperative diffusion in an elemental system [7].
REFERENCE
1. Kang Xia, Hao Gao, Cong Liu, Jianan Yuan, Jian Sun*, Hui-Tian Wang*, Dingyu Xing, "A novel superhard tungsten nitride predicted by machine-learning accelerated crystal structure search", Sci. Bull. 63, 817 (2018).
2. Hao Gao, Junjie Wang, and Jian Sun*, "Improve the performance of machine-learning potentials by optimizing descriptors", J. Chem. Phys. 150, 244110 (2019).
3. Hao Gao, Junjie Wang, Zhaopeng Guo, Jian Sun*, "Determining dimensionalities and multiplicities of crystal nets" npj Comput. Mater. 6, 143 (2020).
4. Cong Liu, Hao Gao, Yong Wang, Richard J. Needs, Chris J. Pickard, Jian Sun*, Hui-Tian Wang*, Dingyu Xing, "Multiple superionic states in helium-water compounds", Nature Physics 15, 1065 (2019).
5. Cong Liu, Hao Gao, Andreas Hermann, Yong Wang, Maosheng Miao, Chris J. Pickard, Richard J. Needs, Hui-Tian Wang, Dingyu Xing, and Jian Sun*, "Plastic and Superionic Helium Ammonia Compounds under High Pressure and High Temperature", Phys. Rev. X 10, 021007 (2020).
6. Hao Gao, Cong Liu, Andreas Hermann, Richard J. Needs, Chris J. Pickard, Hui-Tian Wang, Dingyu Xing, and Jian Sun*, "Coexistence of plastic and partially diffusive phases in a helium-methane compound", Natl. Sci. Rev. 7, 1540 (2020).
7. Y. Wang et al., "Electronically driven 1D cooperative diffusion in a simple cubic crystal", (submitted).
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Presenters
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Jian Sun
School of Physics, Nanjing University
Authors
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Jian Sun
School of Physics, Nanjing University