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Computational Materials Science
Elsevier Science Publishers B.V.
Computational Materials Science

Elsevier Science Publishers B.V.

0927-0256

Computational Materials Science/Journal Computational Materials ScienceISTPSCIEI
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    Construction of machine-learning Zr interatomic potentials for identifying the formation process of c-type dislocation loops

    Okita, T.Terayama, S.Tsugawa, K.Kobayashi, K....
    9页
    查看更多>>摘要：In this study, a Neural Network Potential (NNP) using an Artificial Neural Network (ANN) was developed for Zr, which is used as fuel claddings in light water reactors. The reference data were obtained through first-principles calculations of various quantities, such as strained hexagonal-closed-packed (hcp) cells, strained face-centered cubic cells, cells containing a vacancy, several vacancies, and surface and gamma-surface energies on all five slip planes in the hcp structures. These data were converted to training data for the ANN, which were invariant to the rotation and translation of the atoms and independent of the number of atoms in the cells. The ANN was defined as a three-layer structure and the number of the nodes was set to 26-12-18-1. The NNP reproduced the firstprinciples calculations, particularly for the shear deformation, vacancy formation energy, surface energies, and gamma-surface energies, with much higher accuracy than any of the existing potentials that have been developed for classical molecular dynamics simulations. The NNP was applied to identify the formation process of c-type dislocation loops in Zr, which is a key microstructure responsible for abrupt increases in hydrogen absorption. The formation process was determined by the balance of the vacancy formation energy, surface energy and the gamma-surface energy on the basal plane, both of which were precisely reproduced only by the NNP developed in this study. The formation process was identified based on the atomistic behavior of the NNP.
      原文链接:
    • NSTL
    • Elsevier

    Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis

    Tranas, RasmusLovvik, Ole MartinTomic, OliverBerland, Kristian...
    9页
    查看更多>>摘要：Low lattice thermal conductivity is essential for high thermoelectric performance of a material. Lattice thermal conductivity is often computed using density functional theory (DFT), typically at a high computational cost. Training machine learning models to predict lattice thermal conductivity could offer an effective procedure to identify low lattice thermal conductivity compounds. However, in doing so, we must face the fact that such compounds can be quite rare and distinct from those in a typical training set. This distinctness can be problematic as standard machine learning methods are inaccurate when predicting properties of compounds with features differing significantly from those in the training set. By computing the lattice thermal conductivity of 122 half-Heusler compounds, using the temperature-dependent effective potential method, we generate a data set to explore this issue. We first show how random forest regression can fail to identify low lattice thermal conductivity compounds with random selection of training data. Next, we show how active selection of training data using feature and principal component analysis can be used to improve model performance and the ability to identify low lattice thermal conductivity compounds. Lastly, we find that active learning without the use of DFT-based features can be viable as a quicker way of selecting samples.
      原文链接:
    • NSTL
    • Elsevier

    Molecular dynamics simulation of the interfacial evolution and whisker growth of copper-tin coating under electrothermal coupling

    Zhang, LongXiong, DengjieLi, JunfengYin, Limeng...
    11页
    查看更多>>摘要：With the development of lead-free electronic devices, the failure caused by the growth of tin whiskers poses a potential threat to the reliability of electronic products. In this study, the modified embedded atomic potential proposed by Baskes was used to simulate the interfacial evolution and the whisker growth of copper and tin coatings under electrothermal coupling by using molecular dynamics. Numerical results show that the increase in electric field intensity and temperature can promote the diffusion of Cu atom to Sn atom, and the intermetallic compounds Cu6Sn5 and Cu3Sn are formed successively at the interface of the coating. Compression stress is formed in the coating, and the whisker is shaped at the weak part of the oxide film on the tin layer surface. The increase in electric field intensity and temperature can accelerate the growth of the whisker. This condition is because the increase in electric field intensity or temperature promotes the formation of intermetallic compounds, providing a greater driving force for the growth of tin whiskers. The results can provide a theoretical basis for the growth mechanism of tin whiskers.
      原文链接:
    • NSTL
    • Elsevier

    2D Ni0.25Mn0.75O2: A high-performance cathode for multivalent ion batteries

    Liepinya, DianaShepard, RobertSmeu, Manuel
    9页
    查看更多>>摘要：Although Li-ion batteries have driven portable energy storage in recent decades, there is increasing concern about their safety, cost, and abundance of constituents. Multivalent ion batteries (MVIBs) have the potential to remedy these issues, but they are limited by the currently known MVIB cathodes, which fail to deliver unanimously favorable voltage, energy density, and diffusion kinetics. We used density functional theory (DFT) to model the performance of Li, Na, Mg, Ca, and Al ions when paired with 2D Ni0.25Mn0.75O2 , a novel cathode that uses increased layer separation to improve on the kinetics of its 3D analog. Our calculations yielded maximum voltages of 3.38 V for Na and 2.7 V for Ca, outperforming 2D NaxMnO2 and NaxNiO2. Diffusion barriers for Li, Na, and Ca are below 300 meV, comparable to existing battery technology and the endpoint 2D cathodes; meanwhile, Mg and Al have prohibitively high diffusion barriers, implying their incompatibility with this cathode. Lastly, density of states calculations and Bader charge analysis show that the cathode becomes conducting following ion adsorption, which is necessary for high-rate performance. 2D Ni0.25Mn0.75O2 maintains performance seen with other 2D transition metal oxides while increasing cathode conductivity, indicating that it is a promising candidate for experimental investigation with Li, Na, and Ca ions.
      原文链接:
    • NSTL
    • Elsevier

    Deep learning potential for superionic phase of Ag2S

    Balyakin, I. A.Sadovnikov, S., I
    8页
    查看更多>>摘要：Artificial neural networks are used for describing potential energy surface of beta-Ag2S silver sulfide. It has allowed performing accurate and fast atomistic simulations for describing behavior of investigated system. We develop neural network potential for high temperature ionic conductor beta-Ag2S using DeePMD approach. Reference ab initio dataset was generated using active learning technique implemented in DP-GEN package. Classical molecular simulations with developed neural network potential were performed. Partial radial distribution function for S-S pair and bond-angle distribution function for S-S-S triplet demonstrate crystalline behavior, while the same functions for Ag-Ag pair and Ag-Ag-Ag triplet demonstrate liquid-like behavior. Mean squared displacement of S atoms indicates absence of diffusion for sulfur atoms, while the same function for Ag atoms has linear form at large times that indicates presence of diffusion for this sort of atoms. Velocity autocorrelation functions for S atoms have oscillatory behavior, while for Ag atoms no oscillations are observed. Comparison of mean squared displacement for S atoms and diffusivity for Ag atoms is performed to other ab initio and classical simulations as well as experimental data and demonstrates good agreement in all the cases. Obtained by active learning technique dataset could be expanded to other Ag2S phases for describing Ag2S in wider range of temperatures. Thus accurate, productive, almost free of parameters and promising for future use model for beta-Ag2S was created.
      原文链接:
    • NSTL
    • Elsevier

    Ordered structure and solute-suppressed atomic ordering in iron-cobalt alloys

    Li, YalinQiang, Wenjiang
    8页
    查看更多>>摘要：The slowly cooled Fe-25 wt% Co alloys generally suffer from poor ductility due to the atomic ordering. Combining DFT calculations and experiments, ordered L60-Fe3Co structure was first demonstrated to crystallize in the slowly cooled similar to 25 wt% Co alloys and lead to brittleness. The stable existence of L60-Fe3Co structure is of great significance to further understand the binary Fe-Co phase diagram. Metal elements (e.g. V and Nb) are generally added into FeCo alloy to improve ductility and workable ability. The toughening mechanism of these solutes is mainly realized by suppressing atomic ordering. The reduced antisite defect energies by V and Nb additions lowers the maximum degree of order and antiphase boundary (APB) energies. The key to suppress atomic ordering is reducing antisite defect energy or site-exchange energy. A comprehensive theoretical understanding on the mechanism of suppressing atomic ordering is helpful to further find alloying elements which simultaneously improve mechanical and magnetic properties for Fe3Co or other ordered alloys.
      原文链接:
    • NSTL
    • Elsevier

    Surface strain and co-doping effect on Sm and Y co-doped BaCeO3 in proton conducting solid oxide fuel cells

    Zhang, FengRen, JunfengChen, MeinaHe, Lei...
    10页
    查看更多>>摘要：Although promising, regulating the surface strain is still immature for enhance the performance of protonconducting materials and no clear law has been found. In this work, surface strain and co-doping effect on dopant segregation, hydration reaction and proton transport of Sm and Y co-doped BaCeO3 (BCYS) in protonconducting solid oxide fuel cells (P-SOFC) was investigated. We found that although the dopant segregation trend is reduced as the surface strain increase from -2% to 2%, which means that a large tensile strain is beneficial to enhance structural stability, oxygen vacancy formation energy and proton binding energy near the BCYS surface do not change monotonously with the surface strain. We found that the fewer electrons around the oxygen atoms before hydrogen adsorption, the more stable the proton. It is worth noting that 1% tensile strain is most favorable for enhancing the degree of surface hydration and proton transport in our calculation results, which helps to weaken the negative effects of the space charge layer formed by the accumulation of positive charges on the surface. The collocation of Sm and Y has a synergistic effect, which means Sm facilitates oxygen vacancy formation, while Y promotes hydration reaction. Moreover, the introduction of Sm and Y can hardly change the electronic conductivity of BCYS, which is conducive to the open circuit voltage of P-SOFC.
      原文链接:
    • NSTL
    • Elsevier

    Analysis of monotonic and cyclic crack tip plasticity for a stationary crack tip in a FCC crystal

    Zirkle, TheodoreMcDowell, David L.
    18页
    查看更多>>摘要：The fields produced at the tip of a Mode I crack in a ductile single crystal have been previously investigated using theoretical, experimental, and numerical methods. Limitations in the material model complexity used in theoretical approaches and difficulties in experimentally measuring in situ crack tip fields invite consideration of numerical crystal plasticity. Prior crystal plasticity analyses of crack tip plasticity have leveraged simple phenomenological constitutive forms and investigated limited loading scenarios. The current work extends prior approaches by using a recently developed face-centered cubic (FCC) crystal plasticity model that considers dislocation substructures and complex back stress evolutions during cyclic loading in concert with a finite element model of a stationary crack tip. The model is used to i) more thoroughly understand the conditions where theoretical analyses remain valid in the context of dislocation interactions and substructure development and ii) explore potential fatigue crack growth driving forces for microstructurally small and physically small cracks. Specific observations are made regarding the observed formation of alternating bands of forward and reverse shear, unique to the present model with dislocation substructure, as well as the influence of ratcheting strain on the cyclic irreversibility of slip and associated correlative fatigue crack growth relations.
      原文链接:
    • NSTL
    • Elsevier

    An atomistic analysis of the effect of grain boundary and the associated deformation mechanisms during plain strain compression of a Cu bicrystal

    Chandra, S.Alankar, A.Kumar, N. N.Samal, M. K....
    10页
    查看更多>>摘要：In this work, atomistic simulations are performed to investigate the dislocation activity during plain strain compression in a face centered cubic (FCC) Cu bicrystal. Analysis techniques involving the use of discrete atomic coordinates to characterize the change in lattice orientations of individual crystals and the resulting dislocation patterns are exploited. Compression induces dislocation activities in the abutting crystals and the grain boundary (GB) poses a significant barrier to dislocation motion. Heterogeneous deformation in the crystals due to the presence of GB instigates appreciable differences in the grain orientation distributions at different stages of deformation. The observed local lattice rotation fields are found to correlate well with the calculated geometrically necessary dislocation distributions computed from per-atom Nye tensor. A close comparison of the obtained results with the corresponding experiments published in the literature on same Cu bicrystal provides unique insights into the operative nanoscale deformation mechanisms. The ramifications of such modeling approaches in bridging the traditional gap existing between experiments and simulations are discussed.
      原文链接:
    • NSTL
    • Elsevier

    A fixed grid based accurate phase-field method for dendritic solidification in

    Sinhababu, ArijitBhattacharya, Anirban
    14页
    查看更多>>摘要：In this paper, an easily implementable immersed interface method based high-resolution phase-field model is proposed for simulating dendritic growth related problems in complicated geometries. At first, resolution issues of different Fourier Pseudo-spectral based dealiasing schemes are shown for the anisotropic phase field equations at high thermal undercooling conditions using just adequate spatial grid resolution. The problems of aliasing error and spectral leakage are studied using high-order based exponential smoothing spectral filters, which generally occur at low sampling rate situations. A fully dealiased zero padding scheme based anisotropic phase-field method is also developed in conjunction with an optimal third order strong stability preserving Runge-Kutta (SSPRK3) time integration scheme for obtaining more accurate and stable numerical solutions. In the later part, a modified phase-field method is implemented with the indicator function which simulates different crystal growth problems in complex geometries without using non-trivial mesh refinement algorithm. Effect of non-interacting obstacles present in the computational domain can also be readily incorporated in the present numerical model by using the single order parameter based phase-field equations.
      原文链接:
    • NSTL
    • Elsevier