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Bayesian inference of solid-liquid interfacial properties out of equilibrium

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Title: Bayesian inference of solid-liquid interfacial properties out of equilibrium
Authors: Ohno, Munekazu Browse this author →KAKEN DB
Oka, Yukimi Browse this author
Sakane, Shinji Browse this author
Shibuta, Yasushi Browse this author
Takaki, Tomohiro Browse this author
Issue Date: 18-May-2020
Publisher: American Physical Society (APS)
Journal Title: Physical Review E
Volume: 101
Issue: 5
Start Page: 052121
Publisher DOI: 10.1103/PhysRevE.101.052121
Abstract: Solid-liquid interfacial properties out of equilibrium provide the essential information required for understanding and controlling solidification microstructures in metallic materials. However, few studies have attempted to reveal all interfacial properties out of equilibrium in detail. The present study proposes an approach for simultaneously estimating all interfacial properties in a pure metal below the melting point on the basis of the Bayesian inference theory. The solid-liquid interfacial energy, interfacial mobility, and anisotropy parameters in pure Fe are estimated by combining molecular dynamics simulation with phase-field simulation using an ensemble Kalman filter, which is a data assimilation technique. Furthermore, the temperature dependences of all interfacial parameters are computed and discussed. In summary, the proposed multiscale approach integrates atomistic and microstructural simulations within the framework of data science and it has considerable potential for a wide variety of applications in materials engineering.
Rights: Copyright 2020 by The American Physical Society.
Type: article
Appears in Collections:工学院・工学研究院 (Graduate School of Engineering / Faculty of Engineering) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 大野 宗一

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