A5092380931- Machine Learning in Materials Science
- Spectroscopy and Quantum Chemical Studies
- High-pressure geophysics and materials
- Astro and Planetary Science
- Advanced Electron Microscopy Techniques and Applications
- Glass properties and applications
- Energetic Materials and Combustion
- Metallic Glasses and Amorphous Alloys
- Fuel Cells and Related Materials
- Catalysis and Oxidation Reactions
- Material Science and Thermodynamics
- Material Dynamics and Properties
- Geomagnetism and Paleomagnetism Studies
- Advanced Memory and Neural Computing
- Atomic and Subatomic Physics Research
National University of Defense Technology
2022-2024
Modern laboratory techniques like ultrafast laser excitation and shock compression can bring matter into highly nonequilibrium states with complex structural transformation, metallization dissociation dynamics. To understand model the dramatic change of both electronic structures ion dynamics during such dynamic processes, traditional method faces difficulties. Here, we demonstrate ability deep neural network (DNN) to capture atomic local-environment dependence density (DOS) for...
Entropy production in quasi-isentropic compression (QIC) is critically important for understanding the properties of materials under extreme conditions. However, origin and accurate quantification entropy this situation remain long-standing challenges. In work, a framework established partition, their relation to microstructural change QIC. Cu50Zr50 taken as model material, its simulated by molecular dynamics. On basis atomistic simulation-informed physical free energy, thermodynamic path...
Abstract Molecular dynamics (MD) is an indispensable atomistic-scale computational tool widely-used in various disciplines. In the past decades, nearly all ab initio MD and machine-learning have been based on general-purpose central/graphics processing units (CPU/GPU), which are well-known to suffer from their intrinsic “memory wall” “power bottlenecks. Consequently, nowadays calculations with accuracy extremely time-consuming power-consuming, imposing serious restrictions simulation size...
Shock-induced structural transformations in copper exhibit notable directional dependence and anisotropy, but the mechanisms that govern responses of materials with different orientations are not yet well understood. In this study, we employ large-scale non-equilibrium molecular dynamics simulations to investigate propagation a shock wave through monocrystal analyse transformation detail. Our results indicate anisotropic evolution is determined by thermodynamic pathway. A along <mml:math...
The coupling of excited states and ionic dynamics is the basic challenging point for materials response at extreme conditions. In laboratory, intense laser produces transient nature complexity with highly nonequilibrium states, making it extremely difficult interesting both experimental measurements theoretical methods. With inclusion laser-excited we extended ab initio method into direct simulations whole laser-driven microscopic from solid to liquid. We constructed framework combining...