Atomic simulation for influence of helium atom on movement of edge dislocation in nickel

The molecular dynamics （MD） simulation and the modified analytical embedded-atom method （MAEAM） were used to study the influence of a He atom on the movement of the（a/2）？110？{111} edge dislocation in Ni. First, the calculated Burgers vector distribution shows that the equilibrium dissociation distance （Ded） and the stacking fault energy （Esf） between two partial edge dislocations are about 25.95 ？ and 108 mJ/m2, respectively. Then, the obtained formation energies （Ef） of a He atom at some different sites demonstrate that the He atom is attracted and repelled in the tension and compression regions, respectively. And the He？dislocation interaction reveals that an interstitial He atom plays a more significant role in the dislocation movement than a substitutional He atom. Finally, it is found that the movement of an interstitial He atom is apparent as the first partial dislocation bypasses and the edge dislocation offers fast-diffusion path for the migration of a He atom.

Non-equilibrium atomic simulation for Frenkel-Kontorova model with moving dislocation at finite temperature

We apply the heat jet approach to realize atomic simulations at finite temperature for a Frenkel–Kontorova chain with moving dislocation. This approach accurately and efficiently controls the system temperature by injecting thermal fluctuations into the system from its boundaries, without modifying the governing equations for the interior domain. This guarantees the dislocation propagating in the atomic chain without nonphysical damping or deformation. In contrast to the non-equilibrium Nosé–Hoover heat bath, the heat jet approach efficiently suppresses boundary reflections while the moving dislocation and interior waves pass across the boundary. The system automatically returns back to the equilibrium state after all non-thermal motions pass away. We further apply this approach to study the impact of periodic potential and temperature field on the velocity of moving dislocation.

Reverse Transformation in[110]-Oriented Face-Centered-Cubic Single Crystals Studied by Atomic Simulations

Bidirectional transformations,which are achieved by triggering both dynamic forward transformation from the face-centered-cubic(fcc)austenite to the hexagonal-close-packed(hcp)martensite and the reverse transformation from martensite to austenite during cold deformation,have been previously reported in FeMnCoCr-based high-entropy alloys(HEAs).This leads to the permanent refinement of microstructure and hence enhances the work-hardening capacity of alloys.In order to reveal the microscopic mechanism of the reverse transformation in HEAs under deformation,the effect of the sample aspect ratio,i.e.,Z/X,on the evolution of deformation systems in the equi-atomic FeMnCoCrNi alloy with[110]orientation during uniaxial tensile loading along the Z direction is investigated by atomic simulations in this study.When the aspect ratio is 0.5,the reverse transformation is more significant compared with other models,while a good plasticity can still be maintained.We then compare the micromechanical behavior of three fcc single crystals,i.e.,FeMnCoCrNi,FeCuCoCrNi,and pure Cu.The results show that the stacking fault energy plays a major role in the activation of different deformation mechanisms;however,the lattice distortion in the HEA does not significantly affect the activation of deformation systems.Furthermore,for all materials dislocation slip leads to the softening,while strain hardening is attributed to the initiation of multiple deformation mechanisms.The Shockley partials slip leads to bidirectional phase transition,twinning and detwinning in the three materials.Thus,the reverse transformation can occur in all metallic materials where the fcc to hcp phase transformation is the dominant deformation mechanism.These findings contribute to an in-depth understanding of the deformation mechanism in fcc-structured materials under severe plastic deformation and provide theoretical guidance for the design of alloys with superior strength–plasticity combinations.

Stability of Atomic Simulations with Matching Boundary Conditions

.We explore the stability of matching boundary conditions in one space dimension,which were proposed recently for atomic simulations(Wang and Tang,Int.J.Numer.Mech.Eng.,93(2013),pp.1255–1285).For a finite segment of the linear harmonic chain,we construct explicit energy functionals that decay along with time.For a nonlinear atomic chain with its nonlinearity vanished around the boundaries,an energy functional is constructed for the first order matching boundary condition.Numerical verifications are also presented.

Atomic scale KMC simulation of {100} oriented CVD diamond film growth under low substrate temperature—Part I Simulation of CVD diamond film growth under Joe-Badgwell-Hauge model

The growth of (100} oriented CVD (Chemical Vapor Deposition) diamond film under Joe-Badgwell-Hauge (J-B-H) model is simulated at atomic scale by using revised KMC (Kinetic Monte Carlo) method. The results show that: (1) under Joe's model, the growth mechanism from single carbon species is suitable for the growth of (100) oriented CVD diamond film in low temperature; (2) the deposition rate and surface roughness (Rq) under Joe's model are influenced intensively by temperature (Ta) and not evident bymass fraction W of atom chlorine; (3)the surface roughness increases with the deposition rate, i.e. the film quality becomes worse with elevated temperature, in agreement with Grujicic's prediction; (4) the simulation results cannot make sure the role of single carbon insertion.

Atomic scale KMC simulation of {100} oriented CVD diamond film growth under low substrate temperature-Part Ⅱ Simulation of CVD diamond film growth in C-H system and in Cl-containing systems

The growth of {100}-oriented CVD diamond film under two modifications ofJ-B-H model at low substrate temperatures was simulated by using a revised KMC method at atomicscale. The results were compared both in Cl-containing systems and in C-H system as follows: (1)Substrate temperature can produce an important effect both on film deposition rate and on surfaceroughness; (2) Aomic Cl takes an active role for the growth of diamond film at low temperatures; (3){100}-oriented diamond film cannot deposit under single carbon insertion mechanism, which disagreeswith the predictions before; (4) The explanation of the exact role of atomic Cl is not provided inthe simulation results.

MD simulation of a copper rod under thermal shock

In this paper, thermoelastic problem of onedimensional copper rod under thermal shock is simulated using molecular dynamics method by adopting embedded atom method potential. The rod is on axis x, the left outermost surface of which is traction free and the right outermost surface is fixed. Free boundary condition is imposed on the outermost surfaces in direction y and z. The left and right ends of the rod are subjected to hot and cold baths, respectively. Temperature, displacement and stress distributions are obtained along the rod at different moments, which are shown to be limited in the mobile region, indicating that the heat propagation speed is limited rather than infinite. This is consistent with the prediction given by generalized thermoelastic theory. From simulation results we find that the speed of heat conduction is the same as the speed of thermal stress wave. In the present paper, the simulations are conducted using the large-scale atomic/molecular massively parallel simulator and completed visualization software.

Simulation of Liquid Argon Flow along a Nanochannel： Effect of Applied Force

Liquid argon flow along a nanochannel is studied using molecular dynamics (MD) simulation in this work.Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is used as the MD simulator.The effects of reduced forces at 0.5,1.0 and 2.0 on argon flow on system energy in the form of system potential energy,pressure and velocity profile are described.Output in the form of three-dimensional visualization of the system at steady-state condition using Visual Molecular Dynamics (VMD) is provided to describe the dynamics of the argon atoms.The equilibrium state is reached after 16000 time steps.The effects on system energy,pressure and velocity profile due to reduced force of 2.0 (F2) are clearly distinguishable from the other two lower forces where sufficiently high net force along the direction of the nanochannel for F2 renders the attractive and repulsive forces between the argon atoms virtually non-existent.A reduced force of 0.5 (F0.5) provides liquid argon flow that approaches Poiseuille (laminar) flow as clearly shown by the n-shaped average velocity profile.The extension of the present MD model to a more practical application affords scientists and engineers a good option for simulation of other nanofluidic dynamics processes.

The Erosion Effect of Kapton Film in a Ground-based Atomic Oxygen Irradiation Simulator

In order to investigate the effect of space environmental factors on spacecraft materials, a ground-based simulation facility for space atomic oxygen（AO） irradiation was developed in our laboratory. Some Kapton film samples were subjected to AO beam generated by this facility. The Kapton films before and after AO exposure were analyzed comparatively using optical microscopy, scanning electronic microscopy, atomic force microscopy, high-precision microbalance, and X-ray photoelectron spectroscopy. The experimental results indicate that the transmittance of Kapton film will be reduced by AO irradiation notably, and its color deepens from pale yellow to brown. Surface roughness of the AO-treated sample is already increased obviously after AO irradiation for 5 hours, and exhibits a flannel-like appearance after 15 hours’ exposure in AO beam. The imide rings and benzene rings in kapton molecule are partially decomposed, and some new bonds form during AO irradiation. The mass loss of kapton film increases linearly with the increase of AO fluence, which is resulted from the formation of volatile products, such as CO, CO2 and NOx. The breakage in structure and degradation in properties of AO-treated Kapton film can be attributed to the integrated effect ofimpaction and oxidization of AO beam. The test results agree well with the space flight experimental data.

Atomic-scale simulations in multi-component alloys and compounds:A review on advances in interatomic potential

Multi-component alloys have demonstrated excellent performance in various applications,but the vast range of possible compositions and microstructures makes it challenging to identify optimized alloys for specific purposes.To overcome this challenge,large-scale atomic simulation techniques have been widely used for the design and optimization of multi-component alloys.The capability and reliability of large-scale atomic simulations essentially rely on the quality of interatomic potentials that describe the interactions between atoms.This work provides a comprehensive summary of the latest advances in atomic simulation techniques for multi-component alloys.The focus is on interatomic potentials,including both conventional empirical potentials and newly developed machine learning potentials(MLPs).The fitting processes for different types of interatomic potentials applied to multi-component alloys are also discussed.Finally,the challenges and future perspectives in developing MLPs are thoroughly addressed.Overall,this review provides a valuable resource for researchers interested in developing optimized multicomponent alloys using atomic simulation techniques.

Machine Learning for Chemistry:Basics and Applications

The past decade has seen a sharp increase in machine learning(ML)applications in scientific research.This review introduces the basic constituents of ML,including databases,features,and algorithms,and highlights a few important achievements in chemistry that have been aided by ML techniques.The described databases include some of the most popular chemical databases for molecules and materials obtained from either experiments or computational calculations.Important two-dimensional(2D)and three-dimensional(3D)features representing the chemical environment of molecules and solids are briefly introduced.Decision tree and deep learning neural network algorithms are overviewed to emphasize their frameworks and typical application scenarios.Three important fields of ML in chemistry are discussed:(1)retrosynthesis,in which ML predicts the likely routes of organic synthesis;(2)atomic simulations,which utilize the ML potential to accelerate potential energy surface sampling;and(3)heterogeneous catalysis,in which ML assists in various aspects of catalytic design,ranging from synthetic condition optimization to reaction mechanism exploration.Finally,a prospect on future ML applications is provided.

Stable heat jet approach for temperature control of Fermi-Pasta-Ulam beta chain

In this paper,we propose a stable heat jet approach for accurate temperature control of the nonlinear Fermi-Pasta-Ulam beta(FPU-β)chain.First,we design a stable nonlinear boundary condition,with co-efficients determined by a machine learning technique.Its stability can be proved rigorously.Based on this stable boundary condition,we derive a two-way boundary condition complying with phonon heat source,and construct stable heat jet approach.Numerical tests illustrate the stability of the boundary condition and the effectiveness in eliminating boundary reflections.Furthermore,we extend the bound-ary condition formulation with more atoms,and train the coefficients to eliminate extreme short waves by machine learning technique.Under this extended boundary condition,the heat jet approach is effec-tive for high temperature,and may be adopted for multiscale computation of atomic motion at finite temperature.

From Digital Analogs Through Recursive Machines to Quantum Computer

The report examines the evolution of computers from digital analogs through non-yon Neumann machines to quantum computers, which are also digital analogs. In the 60 years of digital analogs successfully developed at the Institute of Electromechanics of the USSR in Leningrad. An important stage in the development of non-classical multiprocessor machine performance and reliability has been the development of recursive machines, which was carried out at the Institute of Cybernetics led V.M.Glushkov and the Leningrad Institute of Aviation Instrumentation. The general approach to the synthesis is carried out through linguo- combinatorial modeling with structured uncertainty.

Stress relaxation properties of calcium silicate hydrate:a molecular dynamics study

The time-dependent viscoelastic response of cement-based materials to applied deformation is far from fully understood at the atomic level.Calcium silicate hydrate(C-S-H),the main hydration product of Portland cement,is responsible for the viscoelastic mechanism of cement-based materials.In this study,a molecular model of C-S-H was developed to explain the stress relaxation characteristics of C-S-H at different initial deformation states,Ca/Si ratios,temperatures,and water contents,which cannot be accessed experimentally.The stress relaxation of C-S-H occurs regardless of whether it is subjected to initial shear,tensile,or compressive deformation,and shows a heterogeneous characteristic.Water plays a crucial role in the stress relaxation process.A large Ca/Si ratio and high temperature reduce the cohesion between the calcium-silicate layer and the interlayer region,and the viscosity of the interlayer region,thereby accelerating the stress relaxation of C-S-H.The effect of the hydrogen bond network and the morphology of C-S-H on the evolution of the stress relaxation characteristics of C-S-H at different water contents was elucidated by nonaffine mean squared displacement.Our results shed light on the stress relaxation characteristics of C-S-H from a microscopic perspective,bridging the gap between the microscopic phenomena and the underlying atomic-level mechanisms.

Structure and Dynamics of Energy Materials from Machine Learning Simulations:A Topical Review

Energy materials featuring the capability to store and release chemical energy reversibly involve generally complex geometrical structures with multiple elements.It has been a great challenge to establish the quantitative relationship between the structure of materials and their dynamic physicochemical properties.In recent years,machine learning(ML)technique has demonstrated its great power in accelerating the research on energy materials.This topical review introduces the key ingredients and typical applications of ML to energy materials.We mainly focus on the ML based atomic simulation via ML potentials in different architectures/implementations,including high dimensional neural networks(HDNN),Gaussian approximation potential(GAP),moment tensor potentials(MTP)and stochastic surface walking global optimization with global neural network potential(SSW-NN)method.Three cases studies,namely,Si,LiC and LiTiO systems,are presented to demonstrate the ability of ML simulation in assessing the thermodynamics and kinetics of complex material systems.We highlight that the SSW-NN method provides an automated solution for global potential energy surface data collection,ML potential construction and ML simulation,which boosts the current ability for large-scale atomic simulation and thus holds the great promise for fast property evaluation and material discovery.

Atomistic simulations of plasma catalytic processes

There is currently a growing interest in the realisation and optimization of hybrid plasma/catalyst systems for a multitude of applications, ranging from nanotechnology to environmental chemistry. In spite of this interest, there is, however, a lack in fundamental understanding of the underlying processes in such systems. While a lot of experimental research is already being carded out to gain this understanding, only recently the first simulations have appeared in the literature. In this contribution, an overview is presented on atomic scale simulations of plasma catalytic processes as carried out in our group. In particular, this contribution focusses on plasma-assisted catalyzed carbon nanostructure growth, and plasma catalysis for greenhouse gas conversion. Attention is paid to what can routinely be done, and where challenges persist.

Anisotropic interaction between self-interstitial atoms and 1/2<111> dislocation loops in tungsten

We investigate the interaction between <111> self-interstitial atoms(SIAs) and 1/2<111> self-interstitial dislocation loops in tungsten(W) via atomistic simulations. We explore the variation of the anisotropic distribution of binding energies with the shapes and sizes of the 1/2[111] loop and the nonequivalent configurations of <111> SIAs. For an arbitrarily shaped loop, SIA can be more easily trapped in the concave region of the loop than the convex region, which forms a loop whose curvature is closer to that of a circular loop. The direction of SIAs can largely affect the interaction behaviors with the loop. The capture distance of an SIA by the edge of a circular-shaped 1/2[111] loop is clearly elongated along the direction of the SIA;however, it weakly depends on the size of the loop. Then, we analyze the slanted ring-like capture volume of <111> SIAs formed by the circular loop based on their generated anisotropic stress fields. Furthermore, the binding energies obtained from the elastic theory and atomistic simulations are compared. The results provide a reasonable interpretation of the growth mechanism of the loop and the anisotropic interaction that induces irregular-shaped capture volume, affording an insight into the numerical and Object Kinetic Monte Carlo simulations to evaluate the long-term and large-scale microstructural evolution and mechanical properties of W.

Probing deformation mechanisms of gradient nanostructured CrCoNi medium entropy alloy

The gradient nanostructured medium entropy alloys(MEAs) exhibit a good yielding strength and great plasticity. Here, the mechanical properties, microstructure, and strain gradient in the gradient nanostructured MEA CrCoNi are studied by atomic simulations. The strong gradient stress and strain always occur in the deformed gradient nanograined MEA CrCoNi. The origin of improving strength is attributed to the formation of the 9 R phase, deformation twinning, as well as the fcc to hcp phase transformation, which prevent strain localization. A microstructure-based predictive model reveals that the lattice distortion dependent solid-solution strengthening and grain-boundary strengthening dominate the yield strength,and the dislocation strengthening governs the strain hardening. The present result provides a fundamental understanding of the gradient nanograined structure and plastic deformation in the gradient nanograined MEA, which gives insights for the design of MEAs with higher strengths.

Chemical-element-distribution-mediated deformation partitioning and its control mechanical behavior in high-entropy alloys

The chemical element distributions always strongly affect the deformation mechanisms and mechanical properties of alloying materials.However,the detailed atomic origin still remains unknown in highentropy alloys(HEAs)with a stable random solid solution.Here,considering the effect of elemental fluctuation distribution,the deformation behavior and mechanical response of the widely-studied equimolar random Co Cr Fe Mn Ni HEA are investigated by atomic simulations combined with machine learning and micro-pillar compression experiments.The elemental anisotropy factor is proposed,and then used to evaluate the chemical element distribution.The experimental and simulation results show that the local variations of chemical compositions exist and play a critical role in the deformation partitioning and mechanical properties.The high strength and good plasticity of HEAs are obtained via tuning the chemical element distributions,and the optimal elemental anisotropy factor ranges from 2.9 to 3 using machine learning.This trend can be attributed to the cooperative mechanisms depending on the local variational composition:massive partial dislocation multiplication at an initial stage of plastic deformation,and the inhibition of localized shear banding via the nucleation of deformation twinning at a later stage.Using the new insights gained here,it would be possible to create new metallic alloys with superior properties through thermal-mechanical treatment to tailoring the chemical element distribution.