A5088745537- High-pressure geophysics and materials
- Machine Learning in Materials Science
- Quantum, superfluid, helium dynamics
- Diamond and Carbon-based Materials Research
- Advanced Chemical Physics Studies
- Astro and Planetary Science
- Material Dynamics and Properties
- Metal and Thin Film Mechanics
- Spectroscopy and Quantum Chemical Studies
- Thermal properties of materials
- Thermal Expansion and Ionic Conductivity
- nanoparticles nucleation surface interactions
- Nonlinear Optical Materials Studies
- Laser-induced spectroscopy and plasma
- Computational Drug Discovery Methods
- Magnesium Alloys: Properties and Applications
- Sensor Technology and Measurement Systems
- Boron and Carbon Nanomaterials Research
- Metallic Glasses and Amorphous Alloys
- Liver physiology and pathology
- Spacecraft and Cryogenic Technologies
- Ion-surface interactions and analysis
- Laser-Ablation Synthesis of Nanoparticles
- Protein Structure and Dynamics
- Advanced Thermoelectric Materials and Devices
National University of Defense Technology
2020-2025
Beijing Microelectronics Technology Institute
2024
The University of Texas Southwestern Medical Center
2023
Shanghai Jiao Tong University
2023
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version offers numerous advanced features, such DeepPot-SE, attention-based hybrid descriptors, ability to fit tensile properties, type embedding, model...
Ion dynamics exhibits inherent multiscale characteristics because it contains both atomistic and hydrodynamic behaviors. Although atomic-scale ab initio molecular is the subject of intense research on warm dense matter, macroscopic relaxation process contained in zero-frequency mode ionic dynamic structure factor (DSF) cannot be demonstrated due to limitation simulation sizes. Here, we fill this gap via machine-learning deep potential method. To capture ion near limit with accuracy, an...
Lattice thermal conductivity ( κ lat ) of MgSiO 3 perovskite and post-perovskite is an important parameter for the dynamics in Earth. Here, we develop a deep potential density functional theory quality under entire thermodynamic conditions lower mantle, calculate by Green–Kubo relation. Deep molecular captures full-order anharmonicity considers ill-defined phonons low- materials ignored phonon gas model. The shows negative temperature dependence positive linear pressure dependence....
The two-dimensional post-transition-metal chalcogenides, particularly indium selenide (InSe), exhibit salient carrier transport properties and evince extensive interest for broad applications. A comprehensive understanding of thermal is indispensable management. However, theoretical predictions on in the InSe system are found disagreement with experimental measurements. In this work, we utilize both Green-Kubo approach deep potential (GK-DP), together phonon Boltzmann equation density...
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...
Accurate knowledge of the equation state (EOS) deuterium–tritium (DT) mixtures is critically important for inertial confinement fusion (ICF). Although study EOS an old topic, there a longstanding lack global accurate data DT within unified theoretical framework. fuel goes through very wide ranges density and temperature from cold condensed to hot dense plasma where ions are in moderately or even strongly coupled electrons partially degenerate state. The biggest challenge faced when using...
The dynamic electron–ion collisions play an important role in determining the static and transport properties of warm dense matter (WDM). electron force field (EFF) method is applied to study ionic hydrogen. Compared with results from quantum molecular dynamics orbital-free dynamics, diffusions are largely reduced by involving electrons ions. This physics verified Langevin (QLMD) simulations, which includes collision-induced friction (EI-CIF) into equation Based on these new results, we...
The electronic structures of metals undergo transient nonequilibrium states during the photoexcitation process caused by isochoric heating X-ray free-electron laser, and their lattice stability is, thus, significantly affected. By going beyond frozen core approximation, we manually introduced electron distribution function in finite-temperature density functional theory with framework Kohn–Sham–Mermin to investigate such states, effect on is demonstrated phonon dispersion calculated using...
Twinning is a deformation mechanism that creates three-dimensional (3D) twin domains through the migration of facets. This occurs via nucleation and glide twinning disconnections (TDs), which can pile up to create A comprehensive understanding facets associated with 3D twins, including their atomic structures energies, crucial for twinning. In this study, we propose molecular statics/dynamics (MS/MD) approach determine characteristic enclosing non-equilibrium/equilibrium {1¯011} domains, has...
A detailed understanding of the material response to rapid compression is challenging and demanding. For instance, element gold under dynamic exhibits complex phase transformations where there exist some large discrepancies between experimental theoretical studies. Here, we combined large-scale molecular dynamics simulations with a deep potential elucidate processes from an atomic level. The constructed by accurately reproducing free energy surfaces density-functional-theory calculations for...
High pressure structural transformation of copper (Cu) is a rather complex physical process. One the intriguing questions that are rarely discussed comparison between quasi-isentropic response and adiabatic for lattice transition. The ambient face-centered-cubic structure Cu predicted to persist over 100 TPa from ab inito calculations experimentally demonstrated until 1.15 in ramp compression 150 GPa static compression. However, novel body-centered-cubic (BCC) order observed merely at 180...
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version offers numerous advanced features such DeepPot-SE, attention-based hybrid descriptors, ability to fit tensile properties, type embedding,...
Liquid iron is the major component of planetary cores. Its structure and dynamics under high pressure temperature great significance in studying geophysics science. However, for experimental techniques, it still difficult to generate probe such a state matter extreme conditions, while theoretical method like molecular simulation, reliable estimation dynamic properties requires both large simulation size <i>ab initio</i> accuracy, resulting unaffordable computational costs...
In the process of high temperature service, mechanical properties cutting tools decrease sharply due to peeling protective coating. However, mechanism such coating failure remains obscure complicated interaction between atomic structure, temperature, and stress. This dynamic evolution nature demands both large system sizes accurate description on scale, raising challenges for existing scale calculation methods. Here, we developed a deep neural network (DNN) potential Ti-N binary systems...
The accumulation and circulation of carbon-hydrogen dictate the chemical evolution ice giant planets. Species separation diamond precipitation have been reported in systems, verified by static shock-compression experiments. Nevertheless, dynamic formation processes for above-mentioned phenomena are still insufficiently understood. Here, combing deep learning model, we demonstrate that diamonds form through a three-step process involving decomposition, species nucleation procedures. Under...
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...
Superionic ices with highly mobile protons within the stable oxygen sub-lattice occupy an important proportion of phase diagram ice and widely exist in interior icy giants throughout universe. Understanding thermal transport superionic is vital for evolution planets. However, it challenging due to extreme thermodynamic conditions dynamical nature protons, beyond capability traditional lattice dynamics empirical potential molecular approaches. In this work, by utilizing deep approach, we...
The immiscibility of hydrogen-helium mixture under the temperature and pressure conditions planetary interiors is crucial for understanding structures gas giant planets (e.g., Jupiter Saturn). While experimental probe at such extreme challenging, theoretical simulation heavily relied in an effort to unravel mixing behavior hydrogen helium. Here we develop a method via machine learning accelerated molecular dynamics quantify physical separation helium interiors. line achieved with developed...
Thermal conductivity $\kappa$ of MgO plays a fundamental role in understanding the thermal evolution and mantle convection interior terrestrial planets. However, previous theoretical calculations deviate from each other high-pressure B2 phase remains undetermined. Here, by combining molecular dynamics deep potential trained with first-principles data, we systematically investigate ambient state to core-mantle boundary (CMB) super-Earth $5M_{\oplus}$. We point out significance 4-phonon...