Molecular dynamics(MD)is a powerful method widely used in materials science and solid-state physics.The accuracy of MD simulations depends on the quality of the interatomic potentials.In this work,a special class of e...Molecular dynamics(MD)is a powerful method widely used in materials science and solid-state physics.The accuracy of MD simulations depends on the quality of the interatomic potentials.In this work,a special class of exact solutions to the equations of motion of atoms in a body-centered cubic(bcc)lattice is analyzed.These solutions take the form of delocalized nonlinear vibrational modes(DNVMs)and can serve as an excellent test of the accuracy of the interatomic potentials used in MD modeling for bcc crystals.The accuracy of the potentials can be checked by comparing the frequency response of DNVMs calculated using this or that interatomic potential with that calculated using the more accurate ab initio approach.DNVMs can also be used to train new,more accurate machine learning potentials for bcc metals.To address the above issues,it is important to analyze the properties of DNVMs,which is the main goal of this work.Considering only the point symmetry groups of the bcc lattice,34 DNVMs are found.Since interatomic potentials are not used in finding DNVMs,they are exact solutions for any type of potential.Here,the simplest interatomic potentials with cubic anharmonicity are used to simplify the analysis and to obtain some analytical results.For example,the dispersion relations for small-amplitude phonon modes are derived,taking into account interactions between up to the fourth nearest neighbor.The frequency response of the DNVMs is calculated numerically,and for some DNVMs examples of analytical analysis are given.The energy stored by the interatomic bonds of different lengths is calculated,which is important for testing interatomic potentials.The pros and cons of using DNVMs to test and improve interatomic potentials for metals are discussed.Since DNVMs are the natural vibrational modes of bcc crystals,any reliable interatomic potential must reproduce their properties with reasonable accuracy.展开更多
To explore atomic-level phenomena in the Cu-Ni-Sn alloy,a second nearest-neighbor modified embedded-atom method(2NN MEAM)potential has been developed for the Cu-Ni-Sn system,building upon the work of other researchers...To explore atomic-level phenomena in the Cu-Ni-Sn alloy,a second nearest-neighbor modified embedded-atom method(2NN MEAM)potential has been developed for the Cu-Ni-Sn system,building upon the work of other researchers.This potential demonstrates remarkable accuracy in predicting the lattice constant,with a relative error of less than 0.5%when compared to density functional theory(DFT)results,and it achieves a 10%relative error in the enthalpy of formation compared to experimental data,marking substantial advancements over prior models.The bulk modulus is predicted with a relative error of 8%compared to DFT.Notably,the potential effectively simulates the processes of melting and solidification of Cu-15Ni-8Sn,with a simulated melting point that closely aligns with the experimental value,within a 7.5%margin.This serves as a foundation for establishing a 2NN MEAM potential for a flawless Cu-Ni-Sn system and its microalloying systems.展开更多
Molecular Dynamics(MD)simulation for computing Interatomic Potential(IAP)is a very important High-Performance Computing(HPC)application.MD simulation on particles of experimental relevance takes huge computation time,...Molecular Dynamics(MD)simulation for computing Interatomic Potential(IAP)is a very important High-Performance Computing(HPC)application.MD simulation on particles of experimental relevance takes huge computation time,despite using an expensive high-end server.Heterogeneous computing,a combination of the Field Programmable Gate Array(FPGA)and a computer,is proposed as a solution to compute MD simulation efficiently.In such heterogeneous computation,communication between FPGA and Computer is necessary.One such MD simulation,explained in the paper,is the(Artificial Neural Network)ANN-based IAP computation of gold(Au_(147)&Au_(309))nanoparticles.MD simulation calculates the forces between atoms and the total energy of the chemical system.This work proposes the novel design and implementation of an ANN IAP-based MD simulation for Au_(147)&Au_(309) using communication protocols,such as Universal Asynchronous Receiver-Transmitter(UART)and Ethernet,for communication between the FPGA and the host computer.To improve the latency of MD simulation through heterogeneous computing,Universal Asynchronous Receiver-Transmitter(UART)and Ethernet communication protocols were explored to conduct MD simulation of 50,000 cycles.In this study,computation times of 17.54 and 18.70 h were achieved with UART and Ethernet,respectively,compared to the conventional server time of 29 h for Au_(147) nanoparticles.The results pave the way for the development of a Lab-on-a-chip application.展开更多
Al,Ca,and Zn are representative commercial alloying elements for Mg alloys.To investigate the effects of these elements on the deformation and recrystallization behaviors of Mg alloys,we develop interatomic potentials...Al,Ca,and Zn are representative commercial alloying elements for Mg alloys.To investigate the effects of these elements on the deformation and recrystallization behaviors of Mg alloys,we develop interatomic potentials for the Al-Ca,Al-Zn,Mg-Al-Ca and Mg-Al-Zn systems based on the second nearest-neighbor modified embedded-atom method formalism.The developed potentials describe structural,elastic,and thermodynamic properties of compounds and solutions of associated alloy systems in reasonable agreement with experimental data and higher-level calculations.The applicability of these potentials to the present investigation is confirmed by calculating the generalized stacking fault energy for various slip systems and the segregation energy on twin boundaries of the Mg-Al-Ca and Mg-Al-Zn alloys,accompanied with the thermal expansion coefficient and crystal structure maintenance of stable compounds in those alloys.展开更多
One of the major tasks in a molecular dynamics （MD） simulation is the selection of adequate potential functions, from which forces are derived. If the potentials do not model the behaviour of the atoms correctly, th...One of the major tasks in a molecular dynamics （MD） simulation is the selection of adequate potential functions, from which forces are derived. If the potentials do not model the behaviour of the atoms correctly, the results produced from the simulation would be useless. Three popular potentials, namely, Lennard-Jones （L J）, Morse, and embedded-atom method （EAM） potentials, were employed to model copper workpiece and diamond tool in nanometric machining. From the simulation results and further analysis, the EAM potential was found to be the most suitable of the three potentials. This is because it best describes the metallic bonding of the copper atoms; it demonstrated the lowest cutting force variation, and the potential energy is most stable for the EAM.展开更多
Abstract The process of γ＇ phase precipitating from Ni75Al14MO11 is studied by a computational simulation technique based on microscopic phase-field kinetics model. We studied the phase transformation with the purpo...Abstract The process of γ＇ phase precipitating from Ni75Al14MO11 is studied by a computational simulation technique based on microscopic phase-field kinetics model. We studied the phase transformation with the purpose of clarifying the influence of the nearest interatomic potential V Ni-Al （the nearest interatomic potential） on the precipitation process of γ＇ phase. The result demonstrates that there are two kinds of ordered phases, respective Llo and L12 in the early stage, and Llo phase transforms into L12 phase subsequently. For L12 phase, Ni atoms mainly occupy α site （face center positions）, while Al and Mo atoms occupy fl sites （the vertex positions）. When VNi-Al is increased by 10 MeV, the occupation probability of Ni atoms on α sites and Al atoms on β sites are enhanced. Enhanced VNi-Al facilitates clustering and ordering of Al atom, which promotes the formation of the γ＇ phase. At last, the simulation result was discussed by employing the thermodynamic stability.展开更多
The lattice-inversion embedded-atom-method interatomic potential developed previously by us is extended to alkaline metals including Li,Na,and K.It is found that considering interatomic interactions between neighborin...The lattice-inversion embedded-atom-method interatomic potential developed previously by us is extended to alkaline metals including Li,Na,and K.It is found that considering interatomic interactions between neighboring atoms of an appropriate distance is a matter of great significance in constructing accurate embedded-atom-method interatomic potentials,especially for the prediction of surface energy.The lattice-inversion embedded-atom-method interatomic potentials for Li,Na,and K are successfully constructed by taking the fourth-neighbor atoms into consideration.These angular-independent potentials markedly promote the accuracy of predicted surface energies,which agree well with experimental results.In addition,the predicted structural stability,elastic constants,formation and migration energies of vacancy,and activation energy of vacancy diffusion are in good agreement with available experimental data and first-principles calculations,and the equilibrium condition is satisfied.展开更多
We applied an approach to the development of many-body interatomic potentials for NiZr alloys,gaining an improved accuracy and reliability.The functional form of the potential is that of the embedded method,but it has...We applied an approach to the development of many-body interatomic potentials for NiZr alloys,gaining an improved accuracy and reliability.The functional form of the potential is that of the embedded method,but it has been improved as follows. (1) The database used for the development of the potential includes both experimental data and a large set of energies of different structures of the alloys generated by Fab initio calculations. (2) The optimum parametrization of the potential for the given database is obtained by fitting. Using this approach we developed reliable interatomic potentials for Ni and Zr. The potential accurately reproduces basic equilibrium properties of the alloys.展开更多
Motivated by the special theory of gradient elasticity (GradEla), a proposal is advanced for extending it to construct gradient models for interatomic potentials, commonly used in atomistic simulations. Our focus is o...Motivated by the special theory of gradient elasticity (GradEla), a proposal is advanced for extending it to construct gradient models for interatomic potentials, commonly used in atomistic simulations. Our focus is on London’s quantum mechanical potential which is an analytical expression valid until a certain characteristic distance where “attractive” molecular interactions change character and become “repulsive” and cannot be described by the classical form of London’s potential. It turns out that the suggested internal length gradient (ILG) generalization of London’s potential generates both an “attractive” and a “repulsive” branch, and by adjusting the corresponding gradient parameters, the behavior of the empirical Lennard-Jones potentials is theoretically captured.展开更多
So far, it has been a challenge for existing interatomic potentials to accurately describe a wide range of physical properties and maintain reasonable efficiency. In this work, we develop an interatomic potential for ...So far, it has been a challenge for existing interatomic potentials to accurately describe a wide range of physical properties and maintain reasonable efficiency. In this work, we develop an interatomic potential for simulating radiation damage in body-centered cubic tungsten by employing deep potential, a neural network-based deep learning model for representing the potential energy surface. The resulting potential predicts a variety of physical properties consistent with first-principles calculations, including phonon spectrum, thermal expansion, generalized stacking fault energies, energetics of free surfaces, point defects, vacancy clusters, and prismatic dislocation loops. Specifically, we investigated the elasticity-related properties of prismatic dislocation loops, i.e., their dipole tensors, relaxation volumes, and elastic interaction energies. This potential is found to predict the maximal elastic interaction energy between two 1/2 <1 1 1> loops better than previous potentials, with a relative error of only 7.6%. The predicted threshold displacement energies are in reasonable agreement with experimental results, with an average of 128 eV. The efficiency of the present potential is also comparable to the tabulated gaussian approximation potentials and modified embedded atom method potentials, meanwhile, can be further accelerated by graphical processing units. Extensive benchmark tests indicate that this potential has a relatively good balance between accuracy, transferability, and efficiency.展开更多
Machine-learning interatomic potentials have revolutionized materials modeling at the atomic scale.Thanks to these,it is now indeed possible to perform simulations of ab initio quality over very large time and length ...Machine-learning interatomic potentials have revolutionized materials modeling at the atomic scale.Thanks to these,it is now indeed possible to perform simulations of ab initio quality over very large time and length scales.More recently,various universal machine-learning models have been proposed as an out-of-box approach avoiding the need to train and validate specific potentials for each particular material of interest.In this paper,we review and evaluate four different universal machine-learning interatomic potentials(uMLIPs),all based on graph neural network architectures which have demonstrated transferability from one chemical system to another.The evaluation procedure relies on data both from a recent verification study of density-functional-theory implementations and from the Materials Project.Through this comprehensive evaluation,we aim to provide guidance to materials scientists in selecting suitable models for their specific research problems,offer recommendations for model selection and optimization,and stimulate discussion on potential areas for improvement in current machinelearning methodologies in materials science.展开更多
The functional properties of ABO_(3)-type perovskite materials have garnered extensive attention,yet their solidification properties have remained challenging to investigate due to high-temperature environments and ch...The functional properties of ABO_(3)-type perovskite materials have garnered extensive attention,yet their solidification properties have remained challenging to investigate due to high-temperature environments and characterization limitations.In this study,molecular dynamics simulations are employed to comprehensively explore the melting,quenching,and crystal growth processes of SrTiO_(3)(STO)structural evolution.Through iterative fitting and optimization of ion effective charge,a set of potential functions capable of accurately simulating the high-temperature melting of STO are derived.The melting point obtained for STO(2403 K)using the two-phase coexistence method closely corresponds to the empirical value(2333 K),affirming the precision of the optimized potential.Quenching the molten STO yields an amorphous structure characterized primarily by Ti-O six-fold coordination,which increased by 13.09% when reduced to 300 K at a cooling rate of 0.1 K/ps.Notably,the results for different cooling rates revealed that slower cooling rates and lower temperatures yielded more ordered amorphous structures.To circumvent the formation of amorphous states during crystal growth of perovskite materials,we have developed a kinetic two-phase growth(KTPG)method.This approach regulates the cooling rate within a solid-liquid two-phase system,maintaining constant low supercooling at the interface to mimic STO crystal growth kinetics.Cooling at 0.01 K/ps to 1760 K leads to a notable transformation,with the percentage of Ti-O six-fold coordination reaching 90%.This signifies substantial progress in achieving crystal growth through this method,highlighting its efficacy in facilitating crystal formation from the melt phase.展开更多
Liquid metals demonstrate significant potential for applications in thermal management and flexible electronic circuits, necessitating a comprehensive understanding of their transport properties for technological adva...Liquid metals demonstrate significant potential for applications in thermal management and flexible electronic circuits, necessitating a comprehensive understanding of their transport properties for technological advancements. Experimental measurement of these properties presents challenges due to factors like cost, corrosion and impurity control. Consequently, accurate computational simulations become essential for predicting the physical properties of these materials. In this research, molecular dynamics(MD) simulations were employed to model several properties of gallium(Ga), indium(In) and Ga–In alloys, including lattice structural parameters, radial distribution functions(RDF), structure factors, selfdiffusion coefficients and viscosity. Due to the difficulty of traditional interatomic potentials in capturing the short-range interactions directly related to the mechanical behavior of liquid atoms, machine-learning interatomic potentials(MLIPs)have been constructed to precisely describe the liquid metals Ga, In, and Ga–In alloys. This was achieved by utilizing the moment tensor potential(MTP) framework in combination with an active learning strategy. MTP was trained using a comprehensive database generated from DFT and MD simulations, which include a variety of crystal structures, point defects and liquid structures. The calculations of physical properties in this research have shown strong consistency with experimental data, demonstrating that the MTP can accurately describe the interatomic interactions between Ga–Ga, In–In and Ga–In. Our work has established a novel paradigm for investigating the physical properties of various liquid metal systems, offering valuable insights and references for future research.展开更多
This paper presents a new continuum thermal stress theory for crystals based on interatomic potentials.The effect of finite temperature is taken into account via a harmonic model.An EAM potential for copper is adopted...This paper presents a new continuum thermal stress theory for crystals based on interatomic potentials.The effect of finite temperature is taken into account via a harmonic model.An EAM potential for copper is adopted in this paper and verified by computing the effect of the temperature on the specific heat,coefficient of thermal expansion and lattice constant.Then we calculate the elastic constants of copper at finite temperature.The calculation results are in good agreement with experimental data.The thermal stress theory is applied to an anisotropic crystal graphite,in which the Brenner potential is employed.Temperature dependence of the thermodynamic properties,lattice constants and thermal strains for graphite is calculated.The calculation results are also in good agreement with experimental data.展开更多
The structure and properties of materials under neutron irradiation are an important basis in future fusion reactors.In the absence of fusion neutron sources for irradiation experiments,it is increasingly important an...The structure and properties of materials under neutron irradiation are an important basis in future fusion reactors.In the absence of fusion neutron sources for irradiation experiments,it is increasingly important and urgent to carry out neutron irradiation simulations on fusion reactor materials and then establish complete databases of defect properties and collisional cascades,where the first and foremost step is to select suitable interatomic potentials for atomistic-level simulations.In this work,six typic interatomic potentials for tungsten(W)are evaluated and reviewed systematically for radiation damage simulations.The relative lattice stability and elastic constants of bulk W are considered first with those potentials;then,the properties of point defects and defect clusters at interstitial sites and vacancies are obtained by molecular statics/dynam-ics simulations.The formation energies of interstitial/vacancy clusters,1/2<111>and<100>dislocation loops in W and the threshold displacement energies along different directions are also determined.In addition,the extended defects are further investigated,such as free surfaces and the energy profiles of 1/2<111>{110}and 1/2<111>{112}stacking faults.The current results provide a reference for selecting W potentials to simulate the radiation damage.展开更多
This paper summarizes the progress of machine-learning-based interatomic potentials and their applications in advanced manufacturing.Interatomic potential is essential for classical molecular dynamics.The advancements...This paper summarizes the progress of machine-learning-based interatomic potentials and their applications in advanced manufacturing.Interatomic potential is essential for classical molecular dynamics.The advancements made in machine learning(ML)have enabled the development of fast interatomic potential with ab initio accuracy.The accelerated atomic simulation can greatly transform the design principle of manufacturing technology.The most widely used supervised and unsupervised ML methods are summarized and compared.Then,the emerging interatomic models based on ML are discussed:Gaussian approximation potential,spectral neighbor analysis potential,deep potential molecular dynamics,SCHNET,hierarchically interacting particle neural network,and fast learning of atomistic rare events.展开更多
Carbon neutrality has been proposed as a solution for the current severe energy and climate crisis caused by the overuse of fossil fuels, and machine learning(ML) has exhibited excellent performance in accelerating re...Carbon neutrality has been proposed as a solution for the current severe energy and climate crisis caused by the overuse of fossil fuels, and machine learning(ML) has exhibited excellent performance in accelerating related research owing to its powerful capacity for big data processing. This review presents a detailed overview of ML accelerated carbon neutrality research with a focus on energy management, screening of novel energy materials, and ML interatomic potentials(MLIPs), with illustrations of two selected MLIP algorithms: moment tensor potential(MTP) and neural equivariant interatomic potential(NequIP). We conclude by outlining the important role of ML in accelerating the achievement of carbon neutrality from global-scale energy management, unprecedented screening of advanced energy materials in massive chemical space, to the revolution of atomicscale simulations of MLIPs, which has the bright prospect of applications.展开更多
In this paper, we deduce the analytical form of many-body interatomic potentials based on the Green's function in tight-binding representation. The many-body potentials are expressed as the functions of the hoppin...In this paper, we deduce the analytical form of many-body interatomic potentials based on the Green's function in tight-binding representation. The many-body potentials are expressed as the functions of the hopping integrals which are the physical origin of cohesion of atoms. For thesimple case of s-valent system, the inversion of the many-body potentials are discussed in detail by using the lattice inversion method.展开更多
The formation of interphase layers,including the cathode-electrolyte interphase(CEI)and solidelectrolyte interphase(SEI),exhibits significant chemical complexity and plays a pivotal role in determining the performance...The formation of interphase layers,including the cathode-electrolyte interphase(CEI)and solidelectrolyte interphase(SEI),exhibits significant chemical complexity and plays a pivotal role in determining the performance of lithium batteries.Despite considerable advances in simulating the bulk phase properties of battery materials,the understanding of interfaces,including crystalline interfaces that represent the simplest case,remains limited.This is primarily due to challenges in performing ground-state searches for interface microstructures and the high computational costs associated with first-principles methods.Herein,we introduce InterOptimus,an automated workflow designed to efficiently search for ground-state heterogeneous interfaces.InterOptimus incorporates a rigorous,symmetry-aware equivalence analysis for lattice matching and termination scanning.Additionally,it introduces stereographic projection as an intuitive and comprehensive framework for visualizing and classifying interface structures.By integrating universal machine learning interatomic potentials(MLIPs),InterOptimus enables rapid predictions of interface energy and stability,significantly reducing the necessary computational cost in density functional theory(DFT)by over 90%.We benchmarked several MLIPs at three critical lithium battery interfaces,Li_(2)S|Ni_(3)S_(2),LiF|NCM,and Li_(3)PS_(4)|Li,and demonstrated that the MLIPs achieve accuracy comparable to DFT in modeling potential energy surfaces and ranking interface stabilities.Thus,InterOptimus facilitates the efficient determination of ground-state heterogeneous interface structures and subsequent studies of structure-property relationships,accelerating the interface engineering of novel battery materials.展开更多
This paper presents an inverse Monte Carlo method to reconstruct pair interaction potential from pair correlation function. This approach adopts an iterative algorithm on interaction potential to fit known pair correl...This paper presents an inverse Monte Carlo method to reconstruct pair interaction potential from pair correlation function. This approach adopts an iterative algorithm on interaction potential to fit known pair correlation function by compelling deviations of canonical average to meet with Hamiltonian parameters on a basis of statistical mechanism. The effective interaction potential between particles in liquid Ag Rh alloys has been calculated with the inverse Monte Carlo method. It demonstrates an effective and simple way to obtain the effective potential of complex melt systems.展开更多
基金support of the RSF Grant No.24-11-00139(analytics,numerical results,manuscript writing)Daxing Xiong acknowledges the support of the NNSF Grant No.12275116,the NSF Grant No.2021J02051,and the startup fund Grant No.MJY21035For Aleksey A.Kudreyko,this work was supported by the Bashkir StateMedicalUniversity StrategicAcademic Leadership Program(PRIORITY-2030)(analytics).
文摘Molecular dynamics(MD)is a powerful method widely used in materials science and solid-state physics.The accuracy of MD simulations depends on the quality of the interatomic potentials.In this work,a special class of exact solutions to the equations of motion of atoms in a body-centered cubic(bcc)lattice is analyzed.These solutions take the form of delocalized nonlinear vibrational modes(DNVMs)and can serve as an excellent test of the accuracy of the interatomic potentials used in MD modeling for bcc crystals.The accuracy of the potentials can be checked by comparing the frequency response of DNVMs calculated using this or that interatomic potential with that calculated using the more accurate ab initio approach.DNVMs can also be used to train new,more accurate machine learning potentials for bcc metals.To address the above issues,it is important to analyze the properties of DNVMs,which is the main goal of this work.Considering only the point symmetry groups of the bcc lattice,34 DNVMs are found.Since interatomic potentials are not used in finding DNVMs,they are exact solutions for any type of potential.Here,the simplest interatomic potentials with cubic anharmonicity are used to simplify the analysis and to obtain some analytical results.For example,the dispersion relations for small-amplitude phonon modes are derived,taking into account interactions between up to the fourth nearest neighbor.The frequency response of the DNVMs is calculated numerically,and for some DNVMs examples of analytical analysis are given.The energy stored by the interatomic bonds of different lengths is calculated,which is important for testing interatomic potentials.The pros and cons of using DNVMs to test and improve interatomic potentials for metals are discussed.Since DNVMs are the natural vibrational modes of bcc crystals,any reliable interatomic potential must reproduce their properties with reasonable accuracy.
基金sponsored by the Science and Technology Foundation of Guizhou Provincial Education Department(No.QJJ[2024]60)Guizhou Provincial Basic Research Program(Natural Science)(No.QKHJC[2024]Youth 214)+1 种基金Science and Technology Foundation of Guizhou Minzu University(No.GZMUZK[2024]QD21)Research Projects of Anshun University(No.asxybsjj202413).
文摘To explore atomic-level phenomena in the Cu-Ni-Sn alloy,a second nearest-neighbor modified embedded-atom method(2NN MEAM)potential has been developed for the Cu-Ni-Sn system,building upon the work of other researchers.This potential demonstrates remarkable accuracy in predicting the lattice constant,with a relative error of less than 0.5%when compared to density functional theory(DFT)results,and it achieves a 10%relative error in the enthalpy of formation compared to experimental data,marking substantial advancements over prior models.The bulk modulus is predicted with a relative error of 8%compared to DFT.Notably,the potential effectively simulates the processes of melting and solidification of Cu-15Ni-8Sn,with a simulated melting point that closely aligns with the experimental value,within a 7.5%margin.This serves as a foundation for establishing a 2NN MEAM potential for a flawless Cu-Ni-Sn system and its microalloying systems.
文摘Molecular Dynamics(MD)simulation for computing Interatomic Potential(IAP)is a very important High-Performance Computing(HPC)application.MD simulation on particles of experimental relevance takes huge computation time,despite using an expensive high-end server.Heterogeneous computing,a combination of the Field Programmable Gate Array(FPGA)and a computer,is proposed as a solution to compute MD simulation efficiently.In such heterogeneous computation,communication between FPGA and Computer is necessary.One such MD simulation,explained in the paper,is the(Artificial Neural Network)ANN-based IAP computation of gold(Au_(147)&Au_(309))nanoparticles.MD simulation calculates the forces between atoms and the total energy of the chemical system.This work proposes the novel design and implementation of an ANN IAP-based MD simulation for Au_(147)&Au_(309) using communication protocols,such as Universal Asynchronous Receiver-Transmitter(UART)and Ethernet,for communication between the FPGA and the host computer.To improve the latency of MD simulation through heterogeneous computing,Universal Asynchronous Receiver-Transmitter(UART)and Ethernet communication protocols were explored to conduct MD simulation of 50,000 cycles.In this study,computation times of 17.54 and 18.70 h were achieved with UART and Ethernet,respectively,compared to the conventional server time of 29 h for Au_(147) nanoparticles.The results pave the way for the development of a Lab-on-a-chip application.
文摘Al,Ca,and Zn are representative commercial alloying elements for Mg alloys.To investigate the effects of these elements on the deformation and recrystallization behaviors of Mg alloys,we develop interatomic potentials for the Al-Ca,Al-Zn,Mg-Al-Ca and Mg-Al-Zn systems based on the second nearest-neighbor modified embedded-atom method formalism.The developed potentials describe structural,elastic,and thermodynamic properties of compounds and solutions of associated alloy systems in reasonable agreement with experimental data and higher-level calculations.The applicability of these potentials to the present investigation is confirmed by calculating the generalized stacking fault energy for various slip systems and the segregation energy on twin boundaries of the Mg-Al-Ca and Mg-Al-Zn alloys,accompanied with the thermal expansion coefficient and crystal structure maintenance of stable compounds in those alloys.
文摘One of the major tasks in a molecular dynamics （MD） simulation is the selection of adequate potential functions, from which forces are derived. If the potentials do not model the behaviour of the atoms correctly, the results produced from the simulation would be useless. Three popular potentials, namely, Lennard-Jones （L J）, Morse, and embedded-atom method （EAM） potentials, were employed to model copper workpiece and diamond tool in nanometric machining. From the simulation results and further analysis, the EAM potential was found to be the most suitable of the three potentials. This is because it best describes the metallic bonding of the copper atoms; it demonstrated the lowest cutting force variation, and the potential energy is most stable for the EAM.
基金financially supported by the National Natural Science Foundation of China (Nos. 51,204,147 and 51274175)International Cooperation Project Supported by Ministry of Science and Technology of China (No. 2014DFA50320)International Science and Technology Cooperation Project of Shanxi Province (Nos. 2013081017 and 2012081013)
文摘Abstract The process of γ＇ phase precipitating from Ni75Al14MO11 is studied by a computational simulation technique based on microscopic phase-field kinetics model. We studied the phase transformation with the purpose of clarifying the influence of the nearest interatomic potential V Ni-Al （the nearest interatomic potential） on the precipitation process of γ＇ phase. The result demonstrates that there are two kinds of ordered phases, respective Llo and L12 in the early stage, and Llo phase transforms into L12 phase subsequently. For L12 phase, Ni atoms mainly occupy α site （face center positions）, while Al and Mo atoms occupy fl sites （the vertex positions）. When VNi-Al is increased by 10 MeV, the occupation probability of Ni atoms on α sites and Al atoms on β sites are enhanced. Enhanced VNi-Al facilitates clustering and ordering of Al atom, which promotes the formation of the γ＇ phase. At last, the simulation result was discussed by employing the thermodynamic stability.
基金Project supported by the National Basic Research Program of China (Grant No. 2011CB606401)
文摘The lattice-inversion embedded-atom-method interatomic potential developed previously by us is extended to alkaline metals including Li,Na,and K.It is found that considering interatomic interactions between neighboring atoms of an appropriate distance is a matter of great significance in constructing accurate embedded-atom-method interatomic potentials,especially for the prediction of surface energy.The lattice-inversion embedded-atom-method interatomic potentials for Li,Na,and K are successfully constructed by taking the fourth-neighbor atoms into consideration.These angular-independent potentials markedly promote the accuracy of predicted surface energies,which agree well with experimental results.In addition,the predicted structural stability,elastic constants,formation and migration energies of vacancy,and activation energy of vacancy diffusion are in good agreement with available experimental data and first-principles calculations,and the equilibrium condition is satisfied.
基金Supported by the National Natural Science Foundation of China(No.2 9892 16 6 ,2 980 30 0 6 ,2 99830 0 1)
文摘We applied an approach to the development of many-body interatomic potentials for NiZr alloys,gaining an improved accuracy and reliability.The functional form of the potential is that of the embedded method,but it has been improved as follows. (1) The database used for the development of the potential includes both experimental data and a large set of energies of different structures of the alloys generated by Fab initio calculations. (2) The optimum parametrization of the potential for the given database is obtained by fitting. Using this approach we developed reliable interatomic potentials for Ni and Zr. The potential accurately reproduces basic equilibrium properties of the alloys.
文摘Motivated by the special theory of gradient elasticity (GradEla), a proposal is advanced for extending it to construct gradient models for interatomic potentials, commonly used in atomistic simulations. Our focus is on London’s quantum mechanical potential which is an analytical expression valid until a certain characteristic distance where “attractive” molecular interactions change character and become “repulsive” and cannot be described by the classical form of London’s potential. It turns out that the suggested internal length gradient (ILG) generalization of London’s potential generates both an “attractive” and a “repulsive” branch, and by adjusting the corresponding gradient parameters, the behavior of the empirical Lennard-Jones potentials is theoretically captured.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFE03110000)the National Natural Science Foundation of China(Nos.52171084 and 12192282)the Foundation of President of Hefei Institutes of Physical Science,Chinese Academy of Sciences(Nos.YZJJQY202203 and BJPY2021A05).
文摘So far, it has been a challenge for existing interatomic potentials to accurately describe a wide range of physical properties and maintain reasonable efficiency. In this work, we develop an interatomic potential for simulating radiation damage in body-centered cubic tungsten by employing deep potential, a neural network-based deep learning model for representing the potential energy surface. The resulting potential predicts a variety of physical properties consistent with first-principles calculations, including phonon spectrum, thermal expansion, generalized stacking fault energies, energetics of free surfaces, point defects, vacancy clusters, and prismatic dislocation loops. Specifically, we investigated the elasticity-related properties of prismatic dislocation loops, i.e., their dipole tensors, relaxation volumes, and elastic interaction energies. This potential is found to predict the maximal elastic interaction energy between two 1/2 <1 1 1> loops better than previous potentials, with a relative error of only 7.6%. The predicted threshold displacement energies are in reasonable agreement with experimental results, with an average of 128 eV. The efficiency of the present potential is also comparable to the tabulated gaussian approximation potentials and modified embedded atom method potentials, meanwhile, can be further accelerated by graphical processing units. Extensive benchmark tests indicate that this potential has a relatively good balance between accuracy, transferability, and efficiency.
基金supported by the National Key Research and Development Program of China(2022YFE0141100 and 2023YFB3003005).
文摘Machine-learning interatomic potentials have revolutionized materials modeling at the atomic scale.Thanks to these,it is now indeed possible to perform simulations of ab initio quality over very large time and length scales.More recently,various universal machine-learning models have been proposed as an out-of-box approach avoiding the need to train and validate specific potentials for each particular material of interest.In this paper,we review and evaluate four different universal machine-learning interatomic potentials(uMLIPs),all based on graph neural network architectures which have demonstrated transferability from one chemical system to another.The evaluation procedure relies on data both from a recent verification study of density-functional-theory implementations and from the Materials Project.Through this comprehensive evaluation,we aim to provide guidance to materials scientists in selecting suitable models for their specific research problems,offer recommendations for model selection and optimization,and stimulate discussion on potential areas for improvement in current machinelearning methodologies in materials science.
基金support from the Natural Science Foundation of China(Nos.22173047,51931003,and 52130110)the Natural Science Foundation of Jiangsu Province(No.BK20211198)the Fundamental Research Funds for the Central Universities(Nos.30922010905 and 30920041116).
文摘The functional properties of ABO_(3)-type perovskite materials have garnered extensive attention,yet their solidification properties have remained challenging to investigate due to high-temperature environments and characterization limitations.In this study,molecular dynamics simulations are employed to comprehensively explore the melting,quenching,and crystal growth processes of SrTiO_(3)(STO)structural evolution.Through iterative fitting and optimization of ion effective charge,a set of potential functions capable of accurately simulating the high-temperature melting of STO are derived.The melting point obtained for STO(2403 K)using the two-phase coexistence method closely corresponds to the empirical value(2333 K),affirming the precision of the optimized potential.Quenching the molten STO yields an amorphous structure characterized primarily by Ti-O six-fold coordination,which increased by 13.09% when reduced to 300 K at a cooling rate of 0.1 K/ps.Notably,the results for different cooling rates revealed that slower cooling rates and lower temperatures yielded more ordered amorphous structures.To circumvent the formation of amorphous states during crystal growth of perovskite materials,we have developed a kinetic two-phase growth(KTPG)method.This approach regulates the cooling rate within a solid-liquid two-phase system,maintaining constant low supercooling at the interface to mimic STO crystal growth kinetics.Cooling at 0.01 K/ps to 1760 K leads to a notable transformation,with the percentage of Ti-O six-fold coordination reaching 90%.This signifies substantial progress in achieving crystal growth through this method,highlighting its efficacy in facilitating crystal formation from the melt phase.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 12202159 and 12472216)。
文摘Liquid metals demonstrate significant potential for applications in thermal management and flexible electronic circuits, necessitating a comprehensive understanding of their transport properties for technological advancements. Experimental measurement of these properties presents challenges due to factors like cost, corrosion and impurity control. Consequently, accurate computational simulations become essential for predicting the physical properties of these materials. In this research, molecular dynamics(MD) simulations were employed to model several properties of gallium(Ga), indium(In) and Ga–In alloys, including lattice structural parameters, radial distribution functions(RDF), structure factors, selfdiffusion coefficients and viscosity. Due to the difficulty of traditional interatomic potentials in capturing the short-range interactions directly related to the mechanical behavior of liquid atoms, machine-learning interatomic potentials(MLIPs)have been constructed to precisely describe the liquid metals Ga, In, and Ga–In alloys. This was achieved by utilizing the moment tensor potential(MTP) framework in combination with an active learning strategy. MTP was trained using a comprehensive database generated from DFT and MD simulations, which include a variety of crystal structures, point defects and liquid structures. The calculations of physical properties in this research have shown strong consistency with experimental data, demonstrating that the MTP can accurately describe the interatomic interactions between Ga–Ga, In–In and Ga–In. Our work has established a novel paradigm for investigating the physical properties of various liquid metal systems, offering valuable insights and references for future research.
基金supported by the National Natural Science Foundation of China(Grant Nos.11021262,11172303,11132011)National Basic Research Program of China(Grant No.2012CB937500)
文摘This paper presents a new continuum thermal stress theory for crystals based on interatomic potentials.The effect of finite temperature is taken into account via a harmonic model.An EAM potential for copper is adopted in this paper and verified by computing the effect of the temperature on the specific heat,coefficient of thermal expansion and lattice constant.Then we calculate the elastic constants of copper at finite temperature.The calculation results are in good agreement with experimental data.The thermal stress theory is applied to an anisotropic crystal graphite,in which the Brenner potential is employed.Temperature dependence of the thermodynamic properties,lattice constants and thermal strains for graphite is calculated.The calculation results are also in good agreement with experimental data.
基金This work was financially supported by the National MCF Energy R&D Program of China(Grant No.2018YFE0308101)the National Key R&D Program of China(Grant No.2018YFB0704002)the National Natural Science Foundation of China(Grant Nos.51771073,11975260).
文摘The structure and properties of materials under neutron irradiation are an important basis in future fusion reactors.In the absence of fusion neutron sources for irradiation experiments,it is increasingly important and urgent to carry out neutron irradiation simulations on fusion reactor materials and then establish complete databases of defect properties and collisional cascades,where the first and foremost step is to select suitable interatomic potentials for atomistic-level simulations.In this work,six typic interatomic potentials for tungsten(W)are evaluated and reviewed systematically for radiation damage simulations.The relative lattice stability and elastic constants of bulk W are considered first with those potentials;then,the properties of point defects and defect clusters at interstitial sites and vacancies are obtained by molecular statics/dynam-ics simulations.The formation energies of interstitial/vacancy clusters,1/2<111>and<100>dislocation loops in W and the threshold displacement energies along different directions are also determined.In addition,the extended defects are further investigated,such as free surfaces and the energy profiles of 1/2<111>{110}and 1/2<111>{112}stacking faults.The current results provide a reference for selecting W potentials to simulate the radiation damage.
基金This study was supported by the Wuhan University Junior Faculty Research(2042019KF0003)the National Natural Science Foundation of China(51727901,U1501241,and 62174122)+1 种基金the National Key R&D Program of China(2017YFB1103904)the Hubei Provincial Natural Science Foundation of China(2020CFA032).
文摘This paper summarizes the progress of machine-learning-based interatomic potentials and their applications in advanced manufacturing.Interatomic potential is essential for classical molecular dynamics.The advancements made in machine learning(ML)have enabled the development of fast interatomic potential with ab initio accuracy.The accelerated atomic simulation can greatly transform the design principle of manufacturing technology.The most widely used supervised and unsupervised ML methods are summarized and compared.Then,the emerging interatomic models based on ML are discussed:Gaussian approximation potential,spectral neighbor analysis potential,deep potential molecular dynamics,SCHNET,hierarchically interacting particle neural network,and fast learning of atomistic rare events.
基金supported by the National Natural Science Foundation of China (Grant No. 52173234)the Shenzhen Science and Technology Program (Grant Nos. JCYJ20210324102008023 and JSGG202108021534-08024)+3 种基金the Shenzhen-Hong Kong-Macao Technology Research Program(Type C, SGDX2020110309300301)the Natural Science Foundation of Guangdong Province (Grant No. 2022A1515010554)CCF-Tencent Open FundNingbo Municipal Key Laboratory on Clean Energy Conversion Technologies and the Zhejiang Provincial Key Laboratory for Carbonaceous Wastes Processing and Process Intensification Research funded by the Zhejiang Provincial Department of Science and Technology (Grant No. 2020E10018)
文摘Carbon neutrality has been proposed as a solution for the current severe energy and climate crisis caused by the overuse of fossil fuels, and machine learning(ML) has exhibited excellent performance in accelerating related research owing to its powerful capacity for big data processing. This review presents a detailed overview of ML accelerated carbon neutrality research with a focus on energy management, screening of novel energy materials, and ML interatomic potentials(MLIPs), with illustrations of two selected MLIP algorithms: moment tensor potential(MTP) and neural equivariant interatomic potential(NequIP). We conclude by outlining the important role of ML in accelerating the achievement of carbon neutrality from global-scale energy management, unprecedented screening of advanced energy materials in massive chemical space, to the revolution of atomicscale simulations of MLIPs, which has the bright prospect of applications.
文摘In this paper, we deduce the analytical form of many-body interatomic potentials based on the Green's function in tight-binding representation. The many-body potentials are expressed as the functions of the hopping integrals which are the physical origin of cohesion of atoms. For thesimple case of s-valent system, the inversion of the many-body potentials are discussed in detail by using the lattice inversion method.
基金supported by the National Natural Science Foundation of China(92470110)the Special Funds for the Development of Strategic Emerging Industries in Shenzhen(XMHT20240108008)the Shenzhen Stable Support Program for Higher Education Institutions(WDZC20231126215806001)。
文摘The formation of interphase layers,including the cathode-electrolyte interphase(CEI)and solidelectrolyte interphase(SEI),exhibits significant chemical complexity and plays a pivotal role in determining the performance of lithium batteries.Despite considerable advances in simulating the bulk phase properties of battery materials,the understanding of interfaces,including crystalline interfaces that represent the simplest case,remains limited.This is primarily due to challenges in performing ground-state searches for interface microstructures and the high computational costs associated with first-principles methods.Herein,we introduce InterOptimus,an automated workflow designed to efficiently search for ground-state heterogeneous interfaces.InterOptimus incorporates a rigorous,symmetry-aware equivalence analysis for lattice matching and termination scanning.Additionally,it introduces stereographic projection as an intuitive and comprehensive framework for visualizing and classifying interface structures.By integrating universal machine learning interatomic potentials(MLIPs),InterOptimus enables rapid predictions of interface energy and stability,significantly reducing the necessary computational cost in density functional theory(DFT)by over 90%.We benchmarked several MLIPs at three critical lithium battery interfaces,Li_(2)S|Ni_(3)S_(2),LiF|NCM,and Li_(3)PS_(4)|Li,and demonstrated that the MLIPs achieve accuracy comparable to DFT in modeling potential energy surfaces and ranking interface stabilities.Thus,InterOptimus facilitates the efficient determination of ground-state heterogeneous interface structures and subsequent studies of structure-property relationships,accelerating the interface engineering of novel battery materials.
基金Project supported partially by National Natural Science Foundation of China (Grant Nos 50831003 and 50871062)the National Basic Research Program of China (Grant No 2007CB613901)+1 种基金Natural Science Fund for Distinguished Young Scholars of Shandong Province (Grant No JQ200817)National Science Fund for Distinguished Young Scholars (Grant No 50625101)
文摘This paper presents an inverse Monte Carlo method to reconstruct pair interaction potential from pair correlation function. This approach adopts an iterative algorithm on interaction potential to fit known pair correlation function by compelling deviations of canonical average to meet with Hamiltonian parameters on a basis of statistical mechanism. The effective interaction potential between particles in liquid Ag Rh alloys has been calculated with the inverse Monte Carlo method. It demonstrates an effective and simple way to obtain the effective potential of complex melt systems.
