arXiv subjects

Haifeng Song

Publications and source records attributed to Haifeng Song.

At least 19 recordsLinked to original sources

arXiv2026

Unlocking Multi-Component Bulk-Materials Molecular Dynamics with a Small-Footprint Machine Learning Interatomic Potential

Bulk materials, as opposed to nanomaterials, require molecular dynamics (MD) simulations on a large spatial scale (~10^9 atoms or more) to adequately capture their atomic-scale physical properties. Previously, the introduction of machine-learning interatomic potentials (MLIPs) has extended MD to this scale, but even single-component bulk systems require tens of thousands of GPUs on high-end supercomputers. However, multi-component bulk MD simulations remain barely achievable, as the HBM footprint of existing MLIPs - already substantial for single-component systems - grows explosively in multi-component scenarios. This paper proposes an MLIP with a small HBM footprint - less than 3% that of existing MLIPs - unlocking multi-component bulk MD using only hundreds of GPUs. This is achieved by first identifying feature vectors and intermediate tensors as the two primary contributors to HBM footprints in existing MLIPs. To address these two sources, the dimensionality of the feature vectors has been reduced by introducing physical and chemical knowledge, and intermediate tensors have been eliminated by aggressively fusing all kernels into a single mega-kernel. In evaluation, the proposed MLIP has used 144 NVIDIA A100 GPUs to perform MD simulations on a 6-component bulk system with 1.14x10^9 atoms, while previously such MD simulation spatial scale has been restricted to unary systems and typically achieved on high-end supercomputers equipped with tens of thousands of GPUs.

physics.comp-ph↗

arXiv2025

Machine learning-driven elasticity prediction in advanced inorganic materials via convolutional neural networks

Inorganic crystal materials have broad application potential due to excellent physical and chemical properties, with elastic properties (shear modulus, bulk modulus) crucial for predicting materials' electrical conductivity, thermal conductivity and mechanical properties. Traditional experimental measurement suffers from high cost and low efficiency, while theoretical simulation and graph neural network-based machine learning methods--especially crystal graph convolutional neural networks (CGCNNs)--have become effective alternatives, achieving remarkable results in predicting material elastic properties. This study trained two CGCNN models using shear modulus and bulk modulus data of 10987 materials from the Matbench v0.1 dataset, which exhibit high accuracy (mean absolute error <13, coefficient of determination R-squared close to 1) and good generalization ability. Materials were screened to retain those with band gaps between 0.1-3.0 eV and exclude radioactive element-containing compounds. The final predicted dataset comprises two parts: 54359 crystal structures from the Materials Project database and 26305 crystal structures discovered by Merchant et al. (2023 Nature 624 80). Ultimately, this study completed the prediction of shear modulus and bulk modulus for 80664 inorganic crystals. This work enriches existing material elastic data resources and provides robust support for material design, with all data openly available at https://doi.org/10.57760/sciencedb.j00213.00104.

cond-mat.mtrl-sci↗

arXiv2025

A Multi-Level Monte Carlo Tree Search Method for Configuration Generation in Crystalline Systems

In this paper, we study the construction of structural models for the description of substitutional defects in crystalline materials. Predicting and designing the atomic structures in such systems is highly challenging due to the combinatorial growth of atomic arrangements and the ruggedness of the associated landscape. We develop a multi-level Monte Carlo tree search algorithm to generate the "optimal" configuration within a supercell. Our method explores the configuration space with an expanding search tree through random sampling, which further incorporates a hierarchical decomposition of the crystalline structure to accelerate exploration and reduce redundancy. We perform numerical experiments on some typical crystalline systems to demonstrate the efficiency of our method in identifying optimal configurations.

physics.comp-ph↗

arXiv2025

The chemisorption thermodynamics of O$_2$ and H$_2$O on AFM UO$_2$ surfaces unraveled by DFT+U-D3 study

Unraveling the adsorption mechanism and thermodynamics of O$_2$ and H$_2$O on uranium dioxide surfaces is critical for the nuclear fuel storage and uranium corrosion. Based on the first-principles DFT+U-D3 calculations, we carefully test the effect of antiferromagnetic order arrangements on the thermodynamic stability of UO$_2$ surfaces and propose the 1k AFM surface computational model. The chemisorption states of O$_2$ and H$_2$O on UO$_2$ (111) surface, suggested by previous experiments, are accurately calculated for the first time. The adsorption properties of O$_2$ and H$_2$O on UO$_2$(111) and (110) surfaces are discussed in detail to reveal the different interaction mechanisms. Combined with ab initio atomistic thermodynamics method, we systematically calculate the chemisorption phase diagram and isotherm of O$_2$ and H$_2$O on UO$_2$ surfaces. Due to the different intermolecular interactions, the monolayer and multilayer adsorption models are identified for O$_2$ and H$_2$O, respectively. This study has comprehensively revealed the different adsorption mechanisms of O$_2$ and H$_2$O on UO$_2$ surfaces, bridging the electronic structure calculations to the interpretation of experimental results and providing a solid foundation for future theoretical studies of uranium corrosion mechanism in humid air.

cond-mat.mtrl-sci↗

arXiv2024

Mechanism of magnetic phase transition in correlated magnetic metal: insight into itinerant ferromagnet Fe$_{3-\delta}$GeTe$_2$

Developing a comprehensive magnetic theory for correlated itinerant magnets poses challenges due to the difficulty in reconciling both local moments and itinerant electrons. In this work, we investigate the microscopic process of magnetic phase transition in ferromagnetic metal Fe$_{3-\delta}$GeTe$_2$. We find that Hund's coupling is crucial for establishing ferromagnetic order. During the ferromagnetic transition, we observe the formation of quasiparticle flat bands and an opposing tendency in spectral weight transfer, primarily between the lower and upper Hubbard bands, across the two spin channels. Moreover, our results indicate that one of the inequivalent Fe sites exhibits Mott physics, while the other Fe site exhibits Hund's physics, attributable to their distinct atomic environments. We suggest that ferromagnetic order reduces spin fluctuations and makes flat bands near the Fermi level more distinct. The hybridization between the distinctly flat bands and other itinerant bands offers a possible way to form heavy fermion behavior in ferromagnets. The complex interactions of competing orders drive correlated magnetic metals to a new frontier for discovering outstanding quantum states.

cond-mat.str-el↗

arXiv2024

Projected gradient descent algorithm for $\textit{ab initio}$ crystal structure relaxation under a fixed unit cell volume

This paper is concerned with $\textit{ab initio}$ crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and forms the basis of thermodynamic property calculations for materials. The task can be formulated as an energy minimization with a determinant constraint. Widely used line minimization-based methods (e.g., conjugate gradient method) lack both efficiency and convergence guarantees due to the nonconvex nature of the feasible region as well as the significant differences in the curvatures of the potential energy surface with respect to atomic and lattice components. To this end, we propose a projected gradient descent algorithm named PANBB. It is equipped with (i) search direction projections onto the tangent spaces of the nonconvex feasible region for lattice vectors, (ii) distinct curvature-aware initial trial step sizes for atomic and lattice updates, and (iii) a nonrestrictive line minimization criterion as the stopping rule for the inner loop. It can be proved that PANBB favors theoretical convergence to equilibrium states. Across a benchmark set containing 223 structures from various categories, PANBB achieves average speedup factors of approximately 1.41 and 1.45 over the conjugate gradient method and direct inversion in the iterative subspace implemented in off-the-shelf simulation software, respectively. Moreover, it normally converges on all the systems, manifesting its unparalleled robustness. As an application, we calculate the static equations of state for the high-entropy alloy AlCoCrFeNi, which remains elusive owing to 160 atoms representing both chemical and magnetic disorder and the strong local lattice distortion. The results are consistent with the previous calculations and are further validated by experimental thermodynamic data.

physics.comp-ph↗

arXiv2023

An adaptive preconditioning scheme for the self-consistent field iteration and generalized stacking-fault energy calculations

The generalized stacking-fault energy (GSFE) is the fundamental but key parameter for the plastic deformation of materials. We perform first-principles calculations by full-potential linearized augmented planewave (FLAPW) method to evaluate the GSFE based on the single-shift and triple-shift supercell models. Different degrees of defects are introduced in the two models, thereby affecting the convergence of the self-consistent field (SCF) iterations. We present an adaptive preconditioning scheme which can identify the long-wavelength divergence behavior of the Jacobian during the SCF iteration and automatically switch on the Kerker preconditioning to accelerate the convergence. We implement this algorithm in Elk-7.2.42 package and calculate the GSFE curves for Al, Cu, and Si (111) plane <-1-12> direction. We found that the single-shift and triple-shift supercell models have equivalent calculation accuracy and are within the experimental data uncertainty. For computational efficiency, the triple-shift supercell model is preferable due to its better convergence, exhibiting lower degree of defect compared to the single-shift supercell model.

cond-mat.mtrl-sci↗

arXiv2023

TensorMD: Scalable Tensor-Diagram based Machine Learning Interatomic Potential on Heterogeneous Many-Core Processors

Molecular dynamics simulations have emerged as a potent tool for investigating the physical properties and kinetic behaviors of materials at the atomic scale, particularly in extreme conditions. Ab initio accuracy is now achievable with machine learning based interatomic potentials. With recent advancements in high-performance computing, highly accurate and large-scale simulations become feasible. This study introduces TensorMD, a new machine learning interatomic potential (MLIP) model that integrates physical principles and tensor diagrams. The tensor formalism provides a more efficient computation and greater flexibility for use with other scientific codes. Additionally, we proposed several portable optimization strategies and developed a highly optimized version for the new Sunway supercomputer. Our optimized TensorMD can achieve unprecedented performance on the new Sunway, enabling simulations of up to 52 billion atoms with a time-to-solution of 31 ps/step/atom, setting new records for HPC + AI + MD.

physics.comp-ph↗

arXiv2023

Extend the random-walk shielding-potential viscosity model to hot temperature regime

The transport properties of matter have been widely investigated. In particular, shear viscosity over a wide parameter space is crucial for various applications, such as designing inertial confinement fusion (ICF) targets and determining the Rayleigh-Taylor instability. In this work, an extended random-walk shielding-potential viscosity model (ext-RWSP-VM) based on the statistics of random-walk ions and the Debye shielding effect is proposed to elevate the temperature limit of RWSP-VM [Phys. Rev. E 106, 014142] in evaluating the shear viscosity of one component plasma. In the extended model, we reconsider the collision distance that is introduced by hard-sphere concept, hence, it is applicable in wide temperature regime rather than a narrower one in which RWSP-VM is applicable. The results of H, C, Al, Fe, Ge, W, and U show that the extended model provides a systematic way to calculate the shear viscosity of arbitrary one component plasma at the densities from about 0.1 to 10 times the normal density (the density at room temperature and 1 standard atmosphere). This work will help to develop viscosity model in wide regime when combined with our previous low temperature viscosity model [AIP Adv. 11, 015043].

cond-mat.stat-mech↗

arXiv2022

A force-based gradient descent method for $\mathit{\text{ab initio}}$ atomic structure relaxation

Force-based algorithms for $\mathit{\text{ab initio}}$ atomic structure relaxation, such as conjugate gradient methods, usually get stuck in the line minimization processes along search directions, where expensive $\mathit{\text{ab initio}}$ calculations are triggered frequently to test trial positions before locating the next iterate. We present a force-based gradient descent method, WANBB, that circumvents the deficiency. At each iteration, WANBB enters the line minimization process with a trial stepsize capturing the local curvature of the energy surface. The exit is controlled by an unrestrictive criterion that tends to accept early trials. These two ingredients streamline the line minimization process in WANBB. The numerical simulations on nearly 80 systems with good universality demonstrate the considerable compression of WANBB on the cost for the unaccepted trials compared with conjugate gradient methods. We also observe across the board significant and universal speedups as well as the superior robustness of WANBB over several widely used methods. The latter point is theoretically established. The implementation of WANBB is pretty simple, in that no a priori physical knowledge is required and only two parameters are present without tuning.

physics.comp-ph↗

arXiv2022

Melting curve of magnesium up to 460 GPa from ab initio molecular dynamics simulations

Based on ab initio molecular dynamics simulations, we determined the melting curve of magnesium (Mg) up to ~460 GPa using the solid-liquid coexistence method. Between ~30 and 100 GPa, our melting curve is noticeably lower than those from static experiments, but is in good agreement with recent shock experiments. Up to ~450 GPa, our melting curve is generally consistent with the melting points from first-principles calculations using the small-cell coexistence method. We found that, at high pressures of a few hundred GPa, due to the strong softening of interatomic interactions in the liquid phase, solid-liquid coexistence simulations of Mg show some characteristics distinctively different from other metal systems, such as aluminum. For example, at a given volume, the pressure and temperature range for maintaining a stable solid-liquid coexistence state can be very small. The strong softening in the liquid phase also causes the unusual behavior of reentrant melting to occur at very high pressures. The onset of reentrant melting is predicted at ~305 GPa, close to that at ~300 GPa from the small-cell coexistence method. We show that the calculated melting points, considering reentrant melting, can be excellently fitted to a low-order Kechin equation, thereby making it possible for us to obtain a first-principles melting curve of Mg at pressures above 50 GPa for the first time. Similar characteristics in solid-liquid coexistence simulations, as well as reentrant melting, are also expected for other systems with strong softening in the liquid phase at high pressures.

cond-mat.mtrl-sci↗

arXiv2021

Random-walk shielding-potential viscosity model for warm dense metals

We develop a novel model, called the ``random-walk shielding-potential viscosity model'' (RWSP-VM) that introduces the statistics of random-walk ions and the Debye shielding effect to describe the viscosities of warm dense metals. The viscosities of several metals with low to high atomic number (Be, Al, Fe, and U) are calculated using the analytical expression of RWSP-VM. Additionally, we simulate the viscosities of Fe and Be by employing the Langevin molecular dynamics (MD) and classical MD, while the MD data for Al and U are obtained from a previous work. The results of the RWSP-VM are in good agreement with the MD results, which validates the proposed model. Furthermore, we compare the RWSP-VM with the one-component plasma model and Yukawa viscosity model and show that the three models yield results in excellent agreement with each other in the regime where the RWSP-VM is applicable. These results indicate that the RWSP-VM is a universal, accurate, and highly efficient model for calculating the viscosity of metals in the warm dense state. The code of the proposed RWSP-VM is provided, and it is envisaged that it will have broad application prospects in numerous fields.

cond-mat.stat-mech↗

arXiv2020

UO2/BeO interfacial thermal resistance and its effect on fuel thermal conductivity

UO2/BeO interfacial thermal resistance (ITR) is calculated by diffuse mismatch model (DMM) and the effects of ITR on UO2-BeO thermal conductivity are investigated. ITR predicted by DMM is on the order of 10-9 m2K/W. Using this ITR, UO2-BeO thermal conductivities are calculated by theoretical models and compared with experimental data. The results indicate that DMM prediction is applicable to the interface between UO2 and dispersed BeO, while not applicable to the interface between UO2 and continuous BeO. If the thermal conductivity of UO2 containing continuous BeO was to be in agreement with experimental data, its ITR should be on the order of 10-6 - 10-5 m2K/W. Therefore, the vibrational mismatch between UO2 and BeO considered by DMM is the major mechanism for attenuating the heat flux through UO2/dispersed-BeO interface, but not for UO2/continuous-BeO interface. Furthermore, it is found that the presence of ITR leads to the dependence of the thermal conductivity of UO2 containing dispersed BeO on BeO size. With the decrease in BeO size, UO2-BeO thermal conductivity decreases. When BeO size is smaller than a critical value, UO2-BeO thermal conductivity becomes even smaller than UO2 thermal conductivity. For UO2 containing continuous BeO, the thermal conductivity decreases with the decrease in the size of UO2 granule surrounded by BeO, but not necessarily smaller than UO2 thermal conductivity. Under a critical temperature, UO2-BeO thermal conductivity is always larger than UO2 thermal conductivity. Above the critical temperature, UO2-BeO thermal conductivity is larger than UO2 thermal conductivity only when UO2 granule size is large enough. The conditions for achieving the targeted enhancement of UO2 thermal conductivity by doping with BeO are derived. These conditions can be used to design and optimize the distribution, content, size of BeO, and the size of UO2 granule.

physics.app-ph↗

arXiv2020

Spin-Triplet Excitonic Insulator: The Case of Graphone

While various excitonic insulators have been studied in the literature, due to the perceived too-small spin splitting, spin-triplet excitonic insulator is rare. In two-dimensional systems such as a graphone, however, it is possible, as revealed by first-principles calculations coupled with Bethe-Salpeter equation. The critical temperature, given by an effective Hamiltonian, is 11.5 K. While detecting excitonic insulators is still a daunting challenge, the condensation of triplet excitons will result in spin superfluidity, which can be directly measured by a transport experiment. Nonlocal dielectric screening also leads to an unexpected phenomenon, namely, an indirect-to-direct transition crossover between single-particle band and exciton dispersion in graphone, which offers yet another test by experiment.

cond-mat.mtrl-sci↗

arXiv2020

First-Principles Study of Hydrogen Behaviors in $α$-Pu$_{2}$O$_{3}$

The in-depth understanding of hydrogen permeation through plutonium-oxide overlayers is the prerequisite to evaluate the complex hydriding induction period of Pu. In this work, the incorporation, diffusion and dissolution of hydrogen in $α$-Pu$_{2}$O$_{3}$ are investigated by the first-principles calculations and $\textit{ab initio}$ thermodynamic method based on DFT+U and DFT-D3 schemes. Our study reveals that the hydrogen incorporation is endothermic and the separated H atoms prefer to recombine as H$_{2}$ molecules rather than reacting with $α$-Pu$_{2}$O$_{3}$. The H and H$_{2}$ diffusion are both feasible, generally, H will recombine first as H$_{2}$ and then migrate. Both pressure P$_{H2}$ and temperature can promote the hydrogen dissolution in $α$-Pu$_{2}$O$_{3}$. The single H$_{2}$ molecule incorporation and (H+H$_{2}$) mixed dissolution will successively appear when increasing P$_{H2}$. Compared to PuO$_{2}$, this work indicates that Pu sesquioxide is hardly reduced by hydrogen, but the porous $α$-Pu$_{2}$O$_{3}$ facilitates hydrogen transport in Pu oxide layers. We presents the microscopic picture of hydrogen behaviors in the defect-free $α$-Pu$_{2}$O$_{3}$, which could shed some light on the study of the hydriding induction period of Pu.

cond-mat.mtrl-sci↗

arXiv2018

Applicability of Kerker preconditioning scheme to the self-consistent density functional theory calculations of inhomogeneous systems

Kerker preconditioner, based on the dielectric function of homogeneous electron gas, is designed to accelerate the self-consistent field (SCF) iteration in the density functional theory (DFT) calculations. However, question still remains regarding its applicability to the inhomogeneous systems. In this paper, we develop a modified Kerker preconditioning scheme which captures the long-range screening behavior of inhomogeneous systems thus improve the SCF convergence. The effectiveness and efficiency is shown by the tests on long-z slabs of metals, insulators and metal-insulator contacts. For situations without a priori knowledge of the system, we design the a posteriori indicator to monitor if the preconditioner has suppressed charge sloshing during the iterations. Based on the a posteriori indicator, we demonstrate two schemes of the self-adaptive configuration for the SCF iteration.

cond-mat.mtrl-sci↗

arXiv2017

Molecular dynamics simulation of threshold displacement energy and primary damage state in Niobium

In this work, a many-body potential of Nb for radiation damage simulation was developed based on EAM, and most of the point defects of Nb can be predicted properly by this potential. By using the constructed potential, the direction-specific threshold displacement energies (TDE) and displacement cascades up to 20 keV of Nb were performed through molecular dynamics simulations. The calculated results of TDE are in good agreement with previous work for V, Mo and experimental measurements. Lowest TDE was found in <100> direction, and local minas of TDE were found in three low-index directions, which has relation: Ed[100]<Ed[111]<Ed[110]. The evolution of displacement cascades, number of the created point defects, the cascade efficiency the clustering of point defects, and temperature role of these parameters at different PKA energies were systematic investigated. It is found that the cascade efficiency is low and it is can be fitted by a power function as many published work did. The fraction of clustered point defects obtained in this work is low, and only some small clusters were formed at the end of thermal spike. As the temperature increases, the productions of point defects and cascade efficiency were somewhat decreases, however, the fraction of clustered point defects decreases more obvious.

cond-mat.mtrl-sci↗

arXiv2016

Three-dimensional bulk electronic structure of the Kondo lattice CeIn3 revealed by photoemission

We show the three-dimensional electronic structure of the Kondo lattice CeIn3 using soft x-ray angle resolved photoemission spectroscopy in the paramagnetic state. For the first time, we have directly observed the three-dimensional topology of the Fermi surface of CeIn3 by photoemission. The Fermi surface has a complicated hole pocket centred at the Γ-Z line and an elliptical electron pocket centred at the R point of the Brillouin zone. Polarization and photon-energy dependent photoemission results both indicate the nearly localized nature of the 4f electrons in CeIn3, consistent with the theoretical prediction by means of the combination of density functional theory and single-site dynamical meanfield theory. Those results illustrate that the f electrons of CeIn3, which is the parent material of CeMIn5 compounds, are closer to the localized description than the layered CeMIn5 compounds.

cond-mat.str-el↗