1Institute of Applied Physics and Computational Mathematics, Beijing 100088, China
EXTENDED ABSTRACT: There are extreme conditions such as high temperature and high pressure in the research of basic science (high pressure physics, geophysics, material science, etc.) and national engineering (weapons and equipment, fusion physics, etc.), under which the accurate prediction of extreme physical properties of materials is crucial to equipment research and development and component design. In order to improve the prediction ability, the team carried out research on integrated computing methods and applications. (1) Focusing on the modeling of disordered configuration of solid solution alloys and the prediction of physical properties, a similarity function is proposed to describe the similar atomic environment of equivalent atoms, and extended to a generalized similarity function to uniformly describe long-range disorder and shortrange order. The CoCrNi alloy with short-range order is shown more stable by calculations, which is consistent with the experiment; The high pressure phase transformation of MgAl alloy and the compression characteristics of high entropy AlCoFeCrNi alloy were simulated and predicted with the mean field potential method, which were verified by experiments. (2) Focusing on the requirements of high-temperature phase diagram and multiphase physical property prediction, phonon quasiparticle and thermodynamic integration methods were developed and used to study the anharmonic effect and size effect of metallic beryllium. It was found that the anharmonic effect greatly increased the stable pressure range of hcp phase, and solved the controversial problem of high temperature and high pressure hcp/bcc phase boundary of beryllium; It is also found that the predicted melting temperature after overcoming the size effect is lower than the previous FPMD results, which is consistent with the recent impact experiments. (3) Focusing on the demand for efficient and high-precision prediction of high temperature melting, based on the first principles of molecular dynamics, we have developed and improved the efficient melting point prediction method, improved the supercell shape, and optimized the initial configuration of solid liquid coexistence, so that the solid-liquid coexistence method can simulate the accurate melting point in a short time based on smaller systems. The simulation shows that under high pressure of hundreds of GPa, magnesium metal has an abnormal melting behavior due to the strong softening of the interaction potential between liquid atoms of magnesiUlll, that is, the melting temperature decreases with increasing pressure.
Keywords:2D materials; Flux-assisted growth; Material genome; Large grain size
Keywords:Integrated calculation; Extreme conditions; Simulation and prediction
Prof. Haifeng Song is the vice-Dean at Institute of Applied Physics and Computational Mathematics, working on the precise modeling and computations of advanced materials under extreme conditions. His work has been recognized widely and granted the national youth science and technology innovation leader award, the national outstanding youth talent award for DT, the outstanding talent award of Double-Hundred Action of IAPCM, the first grade of national scientific and technological progress award, the YuMin mathematic and physics scientific award, etc. Right now, he is the board member of Computational Materials committee of Chinese Materials Research Society, the technical committee member of Materials Genome Engineering Society, and so on.