Atomistic and continuum modeling of dendritic solidification

Hoyt, J. J.

doi:10.1016/s0927-796x(03)00036-6

Cited by 398 publications

(252 citation statements)

References 165 publications

(302 reference statements)

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“…This is in agreement with the information Table I. Thermodynamic and kinetic parameters estimated from molecular dynamics simulations [41][42][43][44][45][46][47][48][49] Element (potential) 46b Sun et al 45c Asadi et al 48d Asta et al 42e Hoyt et al 41f Hoyt et al 44g Hashimoto et al 47h Asadi et al 49i Morris 43 . in Table I, in which the kinetic coefficient of the h100i direction is larger than that of the h110i direction.…”

Section: Solidification In Large-scale Molecular Dynamics Simulationsupporting

confidence: 83%

“…The estimated values of these properties in representative papers [41][42][43][44][45][46][47][48][49] are summarized in Table I. As can be seen in the table, the kinetic coefficient of the bcc h100i orientation is slightly higher than those of the h110i and h100i orientations in general.…”

Section: Solidification In Large-scale Molecular Dynamics Simulationmentioning

confidence: 99%

“…[41][42][43][44][45][46][47][48][49] In particular, the anisotropy in the interfacial parameters is a key factor determining the morphology of dendrite structures, although there are few reliable experimental values for the degree of anisotropy in the interfacial parameters. Therefore, an important role of molecular dynamics simulations is to provide interfacial parameters estimated from atomic-scale information for use in mesoscale simulations, which is a basic concept of multiscale modeling.…”

Section: Introductionmentioning

confidence: 99%

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Solidification in a Supercomputer: From Crystal Nuclei to Dendrite Assemblages

Shibuta

Ohno

Takaki

2015

JOM

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Thanks to the recent progress in high-performance computational environments, the range of applications of computational metallurgy is expanding rapidly. In this paper, cutting-edge simulations of solidification from atomic to microstructural levels performed on a graphics processing unit (GPU) architecture are introduced with a brief introduction to advances in computational studies on solidification. In particular, million-atom molecular dynamics simulations captured the spontaneous evolution of anisotropy in a solid nucleus in an undercooled melt and homogeneous nucleation without any inducing factor, which is followed by grain growth. At the microstructural level, the quantitative phase-field model has been gaining importance as a powerful tool for predicting solidification microstructures. In this paper, the convergence behavior of simulation results obtained with this model is discussed, in detail. Such convergence ensures the reliability of results of phase-field simulations. Using the quantitative phase-field model, the competitive growth of dendrite assemblages during the directional solidification of a binary alloy bicrystal at the millimeter scale is examined by performing two-and threedimensional large-scale simulations by multi-GPU computation on the supercomputer, TSUBAME2.5. This cutting-edge approach using a GPU supercomputer is opening a new phase in computational metallurgy.

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Section: Solidification In Large-scale Molecular Dynamics Simulationsupporting

confidence: 83%

Section: Solidification In Large-scale Molecular Dynamics Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Solidification in a Supercomputer: From Crystal Nuclei to Dendrite Assemblages

Shibuta

Ohno

Takaki

2015

JOM

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“…The atomistic calculations [9] have established that the parameterizations of anisotropic interface free energy require two anisotropy parameters, as expressed by Eq. (2) ... …”

Section: Anisotropic Interface Free Energy and Interface Stiffnessmentioning

confidence: 99%

“…Recently, molecular dynamics (MD) simulations [9] have established that the parameterization of interface free energy for fcc metals requires two anisotropy parameters ( 1 ,  2 ).…”

Section: Introductionmentioning

confidence: 99%

Orientation selection of equiaxed dendritic growth by three-dimensional cellular automaton model

Wei

Lin

Huang

2012

Physica B: Condensed Matter

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A three-dimensional (3-D) adaptive mesh refinement (AMR) cellular automata (CA) model is developed to simulate the equiaxed dendritic growth of pure substance. In order to reduce the mesh induced anisotropy by CA capture rules, a limited neighbor solid fraction (LNSF) method is presented. An expansion description using two interface free energy anisotropy parameters ( 1 ,  2 ) is used in present 3-D CA model. The dendrite growths with the orientation selection between <100> and <110> are discussed using the different  1 with  2 =-0.02. It is found that the simulated morphologies by present CA model are as expected from the minimum stiffness criterion.

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Importance of Interfacial Energy in Precipitation Modeling Using Computational Thermodynamics Techniques

Silva¹

2015

TMS2015 Supplemental Proceedings

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Atomistic and continuum modeling of dendritic solidification

Cited by 398 publications

References 165 publications

Solidification in a Supercomputer: From Crystal Nuclei to Dendrite Assemblages

Solidification in a Supercomputer: From Crystal Nuclei to Dendrite Assemblages

Orientation selection of equiaxed dendritic growth by three-dimensional cellular automaton model

Importance of Interfacial Energy in Precipitation Modeling Using Computational Thermodynamics Techniques

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