Quantitative modeling of the equilibration of two-phase solid-liquid Fe by atomistic simulations on diffusive time scales

Asadi, Ebrahim; Zaeem, Mohsen Asle; Nouranian, Sasan; Baskes, M. I.

doi:10.1103/physrevb.91.024105

Cited by 75 publications

(50 citation statements)

References 60 publications

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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: 82%

“…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: 82%

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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“…It basically determines the nano-and microstructures and the resultant properties of manufactured materials. Understanding the solid-liquid behavior and determining solid-liquid interface properties [9][10][11] are essential steps towards predicting the nano-and microstructure patterns. It is clear that further fundamental computational and experimental studies are required in order to acquire enough information on solid-liquid properties for different material systems (e.g., alloys).…”

Section: Discussionmentioning

confidence: 99%

Recent Advances in Study of Solid-Liquid Interfaces and Solidification of Metals

Zaeem

2018

Metals

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“…the parameters a; k; q 0 and g for the one-mode PFC model. This quantitative modeling of materials using PFC models has been only explored for modeling of BCC (Fe) [15][16][17][18] and FCC (Ni) [19,20] metals at their melting points and their coexistence with the liquid state. For FCC crystals, Wu et al [19] developed a two-mode PFC model and presented a method to determine its model parameters based on the liquid structure factor and solid density amplitude fluctuation.…”

Section: Introductionmentioning

confidence: 99%