查看更多>>摘要：Titanium nitride (TiN) is used in various applications because of its excellent wear and corrosion resistance. TiN with a rock-salt-type crystal structure has been investigated extensively, but the existence of non-rock-salt-type phases (e.g., Ti2N) has only been reported recently from first-principles calculations. Molecular dynamics (MD) simulation is a powerful tool to predict mechanical properties, but it generally requires interatomic potentials. The conventional many-body interatomic potentials (e.g., modified embedded-atom method (MEAM) potential) for rock-salt TiN are not applicable to these other phases. Hence, in this study, a neural network (NN)-based method to create interatomic potentials is developed, which are referred to as neural network potentials (NNPs); hence, MD simulations can be conducted for TiN and other phases. First, ab initio molecular dynamics (AIMD) simulations are conducted to obtain the relationships between atomic configurations and the corresponding total potential energies and forces on each atom. Subsequently, these relationships are used for the NN to generate NNP. NNP can accurately reproduce the energies and forces calculated by AIMD simulations. The mechanical properties of TiN are computed using the NNP and MD simulation and verified with the MEAM potential and its experiment. Finally, MD simulation using the developed NNP is conducted for the other phase (Ti2N) to investigate its mechanical properties.
查看更多>>摘要：Dissipation and adhesion are important in many areas of materials science, including friction and lubrication, cold spray deposition, and micro-electromechanical systems (MEMS). Another interesting problem is the adhesion of mineral grains during the early stages of planetesimal formation in the early solar system. Molecular-dynamics (MD) simulation has often been used to elucidate dissipative properties, most often in the simulation of sliding friction. In this paper, we demonstrate how the reversible and irreversible work associated with interactions between planar surfaces can be calculated using the dynamical contact simulation approach based on MD and empirical potentials. Moreover, it is demonstrated how the approach can obtain the free-energy delta A(z) as a function of separation between two slabs using the Jarzynksi equality applied to an ensemble of trajectories which deviate significantly from equilibrium. Furthermore, the dissipative work can also be obtained using this method without the need to compute an entire cycle from approach to retraction. It is expected that this technique might be used to efficiently compute dissipative properties which might enable the use of more accurate approaches including density-functional theory. In this paper, we present results obtained for forsterite surfaces both with and without MgO-vacancy surface defects. It is shown that strong dissipation is possible when MgO-vacancy defects are present. The mechanism for strong dissipation is connected to the tendency of less strongly-bound surface units to undergo large displacements including mass transfer between the two surfaces. Systems with strong dissipation tend to exhibit a long-tailed distribution rather than the Gaussian distribution often anticipated in near-equilibrium applications of the JE.
查看更多>>摘要：Thermoelectric materials can contribute to the energy generation by converting thermal into electrical energy. However, current thermoelectrics exhibit low efficiency due to their complex intertwined electrical and thermal properties. Diverse first-principles (based on density functional theory [DFT]) and experimental (based on the single parabolic band [SPB] model) optimization strategies have been explored. However, DFT calculations are limited to simple compounds due to their high computational cost and the SPB model commonly assumes that the electron transport is limited by acoustic phonons. Recent studies, however, revealed that other scattering mechanisms can also be dominant in high-performance thermoelectric materials. Here, a graphical user interface (GUI) is presented, and it allows to optimize the thermoelectric performance based on a scattering-dependent single parabolic band model, TOSSPB. In addition to acoustic deformation potential scattering, polar optical phonon and (screened and non-screened) ionized impurity scattering are included. The GUI indicates that the optimization strategies are strongly dependent on the scattering mechanism which can be obtained using the experimental Hall data and Seebeck coefficient of multiple samples. TOSSPB was tested on the thermoelectric properties of PbTe and SnSe. While the electronic properties of PbTe can be limited by acoustic phonons or polar optical phonons, ionized impurity is most likely the dominant scattering mechanism in hole-doped SnSe as recently predicted. By providing understanding for the scattering mechanism, TOSSPB can tailor the optimization strategies in a wide range of thermoelectric materials accelerating the discovery of high-performance thermoelectrics.
查看更多>>摘要：In this work, we use molecular dynamics simulations to study the enhancement of surface over bulk diffusion (surface enhanced diffusion) in (PbO)(x)(SiO2)(1-x) glasses. This work is motivated to better understand surface diffusion in glasses and its connection to fragility, and to enhance surface diffusion in silica and related glasses for greater thermodynamic stability during vapor-deposition. By adding PbO to silica, the fragility of glass increases continuously for 10% <= x <= 70% during experiments. The increase in fragility may correspond to an increase in surface enhanced diffusion, as fragility and surface diffusion are correlated. We observe that for the silicates investigated, while surface enhanced diffusion increases with fragility, the enhancement is quite small. The slower diffusing Si and O atoms have higher enhancements, which could allow for some surface stabilization effects. We demonstrate that there are only small changes in atomic arrangements, consistent with the similar diffusion rates, at the surface as compared to bulk. Finally, we examine the trend of bulk versus surface diffusion in view of previous observations in organic and metallic glasses and found that in oxides, fragility increase may not be strongly linked to enhanced surface diffusion.
查看更多>>摘要：Nucleation of dislocations in a homogeneous crystal lattice is relevant for small-scale plasticity or ultra-fast loading. Previously, we improved the dislocation nucleation theory and proposed to use artificial neural networks (ANNs) trained by molecular dynamics (MD) data to obtain a self-contained description [1]. The ANNs were used to approximate material properties, such as stress-strain relationship, shear modulus and generalized stacking fault at the elastic stage prior to the nucleation of dislocations. In the present work, we consider the case of copper single crystal in a wide range of pressures from-10 GPa to +50 GPa. At preparation of training data, we apply a polynomial extrapolation of MD data beyond the nucleation limit, which allows us to improve the precision of the trained ANNs and make the theory predictions more accurate. Also we develop an approximate approach, which requires smaller and simpler MD data for training, but gives the strain rate dependence of the nucleation threshold close to the rigorous theory of dislocation nucleation.
El Kacemi, Z.Mansouri, Z.Benyoussef, A.El Kenz, A....
10页
查看更多>>摘要：It is well known that fluorophosphate Na2FePO4F materials unveil promise in battery applications as sodium-ion cathode materials, particularly on account of their non-toxic features, economic and environmental advantages. In this paper, we mainly report on how the electronic conductivity and the voltage of the Na2FePO4F can be enhanced by Mn-doping, leading then to high energy density cathode materials. For this purpose, density functional theory (DFT) calculations are used to investigate the structural, electronic, and electrochemical properties of the pristine and the Mn-doped Na2FePO4F. The obtained results show a decrease of the band gap energy from 2.19 eV to 1.36 eV with the GGA + U approximation and from 2.80 eV to 1.93 eV with the HSE hybrid functional, by doping 50% of the Fe site in the Na2FePO4F lattice with Mn. This indicates an improvement in the electronic conductivity of the pristine material as confirmed by the calculation of effective masses. On the other hand, the Climbing Image Nudged Elastic Band (CI-NEB) calculations unveil a clear drop in the diffusion energies of the three similar paths in doped Na2FePO4F, which indicates the easy transportation of Na+ inside the lattice. The average voltage and quality factor-Q calculations reveal encouraging results for the 50% Mn-doped Na2FePO4F. These findings show the potential of Na2Fe0.5Mn0.5PO4F as a promising cathode material for Na-ion batteries.
查看更多>>摘要：In this work, we study lattice thermal conductivity (k) of BC5, an diamondlike ultra-hard material, using first-principles computations and analyze the effect of both isotopic disorder as well as length scale dependence. k of isotopically pure BC5 is computed to be 169 Wm(-1) K-1 (along a-axis) at 300 K; this high k is found to be due to the high frequencies and phonon group velocities of both acoustic and optical phonons owing to the light atomic mass of Carbon (C) and Boron (B) atoms and strong C-C and B-C bonds. We also observe a dominance of optical phonons (~54%) over acoustic phonons in heat conduction at higher temperatures (~500 K). This unusually high contribution of optical phonons is found to be due to a unique effect in BC5 related to a weaker temperature dependence of optical phonon scattering rates relative to acoustic phonons. The effect is explained in terms of high frequencies of optical phonons causing decay into other high frequency phonons, where low phonon populations cause the decay term to become insensitive to temperature. The effect further leads to high nanoscale thermal conductivity of 77 Wm(-1) K-1 at 100 nm length scale due to optical phonon meanfreepaths being in nanometer regime. These results provide avenues for application of BC5 in nanoscale thermal management.
Gao, YipengAagesen, LarryJokisaari, Andrea M.Zhang, Yongfeng...
10页
查看更多>>摘要：Self-organized microstructures and patterns have been widely observed in non-equilibrium physical systems. In particular, irradiation in metals creates far-from-equilibrium environments, in which the competing dynamics of defect production and annihilation can lead to unique self-organized superlattice structures, e.g., void and gas bubble superlattices. From a physical point of view, the superlattice structures are dictated by the intrinsic symmetry breaking in the metals, i.e., anisotropy caused by the breaking of continuous rotational symmetry. In the literature, two distinctive anisotropies, elastic anisotropy and diffusion anisotropy of interstitials, have been proposed to be the origins of superlattice formation. However, it is still unclear which anisotropy dominates the symmetry selection of superlattice structures. In this paper, we study elastic anisotropy and its effect on the symmetry of void superlattices. By using theoretical analyses and phase field simulations, we show that elastic anisotropy in cubic metals can lead to either face-centered cubic or simple cubic superlattices depending on the Zener anisotropy ratio. The superlattices formed under this elastic anisotropy mechanism must form under the influence of spinodal decomposition, as the mechanism requires perturbations in the vacancy concentration field to develop into spatially-static concentration waves. We compare to existing work on symmetry selection in superlattices via diffusion anisotropy and to experimental observations, and we suggest that concentration wave development under the influence of elastic anisotropy is not the mechanism for symmetry selection during the formation of irradiation-induced void superlattices, but that diffusion anisotropy could be the dominant mechanism.
查看更多>>摘要：A data-driven framework is developed and examined for creating spatially-varying crystallographic textures over component-scale Computer-Aided Design (CAD) models. Here, a set of three orthogonal 2D micrographs of an Additively-Manufactured (AM) specimen are first obtained experimentally through Electron Backscatter Diffraction (EBSD) and subsequently converted to a 3D representative unit cell using the Markov Random Field (MRF) technique. Features such as grain size, crystallographic orientation, and grain boundary misorientation distributions are used to validate the reconstructed 3D microstructure against input experimental EBSD images. The variations of microstructural features during a powder-based additive manufacturing process are subsequently modeled by merging patches from the 3D snapshot of AM microstructural unit cell in a part-scale geometry using a tensor-based optimization process. The optimization algorithm repeatedly pastes microstructural elements from the reconstructed MRF unit cell onto the geometrical CAD domain until it is entirely covered. Here, through a simple Graphical User Interface (GUI), the user specifies a tensor field over the volumetric CAD model, defining the local control over grain-scale, anisotropy, and crystal growth orientation. This new approach provides a workflow for reconstructing global maps of AM microstructures in real-time by embedding site-specific images based on known AM microstructural patterns seen in experimental characterization techniques. The numerical results are helpful specifically for the visualization of process-microstructure relationships in metal additive manufacturing techniques.
查看更多>>摘要：This work presents the simulation approach on the phase transformation and the microstructure evolution of a CrMo steel containing low Si processed with a typical Q & P cycle. The phase transformations at all steps of the Q & P were modelled using kinetics modelling and phase field model in order to predict the austenite grain size, the subsequent fraction and size of microstructural constituents. The initial austenite grain size was predicted considering the solute drag effect due to the presence of Cr obtained from kinetics simulation. The results showed that the austenite grain growth is restricted due to solute drag effect of Cr revealing that the heating stage is important for estimating the austenitic grain size. During quenching, the fraction of initial martensite was predicted. The results were aligned with dilatometry data indicating that the martensite fraction can be predicted via the phase field method. At the partitioning stage, the carbon content in the microstructural constituents determines the fraction of bainitic ferrite and retained austenite at the end of partitioning. In order to predict accurately the carbon content in the microstructure, it is important to simulate the carbon diffusion in the 2nd heating and prior to bainitic transformation. The results showed that the remaining austenite is enriched in carbon. During bainitic transformation, carbon atoms diffuse from bainitic ferrite sheaves towards austenite. By the time C concentration in austenite increases up to para - equilibrium value, austenite is stabilized. Due to fine PAGBs, the enrichment of retained austenite in C can be accelerated; thus smaller partition time can be applied for the stabilization of austenite and to complete the partitioning stage. Phase field results were in agreement with SEM/EBSD results showing that phase transformations can be predicted at all stages of Q & P process.
NSTL
Elsevier