一般講演

[G] Computational Materials Science

Fri. Mar 10, 2023 9:00 AM - 10:45 AM Rm. H (Rm.1212,1st Flr.,Buld.No.12)

座長:大谷博司(公益財団法人豊田理化学研究所)

※表示の講演時間には質疑応答時間も含みます。
（質疑応答時間5分、基調講演と招待講演は5～10分）

+Add all to schedule

9:00 AM - 9:15 AM

[199] Structures of subphase candidates Sm-Cu-Fe in new SmFe₁₂-based magnets

*Soma Nishino¹, Yoshihiro Gohda² (1. Tokyo Tech (Undergrad), 2. Tokyo Tech)

9:15 AM - 9:30 AM

[200] Phase equilibria of B2 Sm-Fe-Cu alloys by cluster-expansion method

*Satoru ENOMOTO¹, Sonju KOU¹, Taichi ABE², Yoshihiro GOHDA¹ (1. Dept. Mater. Sci. Eng., Tokyo Tech, 2. NIMS)

9:30 AM - 9:45 AM

[201] Development of machine learning potential for paramagnetic fcc iron

*Taiki IWAMURA¹, Atsuto SEKO², Isao TANAKA² (1. Kyoto University, 2. Kyoto University)

9:45 AM - 10:00 AM

[202] Prediction of crystal structures under pressure using machine learning potentials

*Hayato WAKAI¹, Atsuto SEKO², Isao TANAKA² (1. Kyoto University, 2. Kyoto University)

10:00 AM - 10:15 AM

[203] Kinetic Monte Carlo analysis on hydrogen trapping by vacancies in B2-type PdCu alloys

*Akihiro Mitsuhara¹, Hiroshi Yukawa², Hajime Kimizuka² (1. Nagoya Univ. (graduate student), 2. Nagoya Univ.)

10:15 AM - 10:30 AM

[204] Quantitative phase-field modeling of interface motion with non-equilibrium solute partitioning

*Munekazu OHNO¹ (1. Hokkaido University)

10:30 AM - 10:45 AM

[205] Time variation of the number of nuclei during homogeneous nucleation and nucleus growth process by CA model

*Takashi ARAI¹, Puwadet Sutipanya (1. National Defense Academy, Department of Applied Physics)

Sessions

11.Computational Science » Atomistic Structures/Microstructures/Properties/Functions

[G] Computational Materials Science

[199] Structures of subphase candidates Sm-Cu-Fe in new SmFe₁₂-based magnets

[200] Phase equilibria of B2 Sm-Fe-Cu alloys by cluster-expansion method

[201] Development of machine learning potential for paramagnetic fcc iron

[202] Prediction of crystal structures under pressure using machine learning potentials

[203] Kinetic Monte Carlo analysis on hydrogen trapping by vacancies in B2-type PdCu alloys

[204] Quantitative phase-field modeling of interface motion with non-equilibrium solute partitioning

[205] Time variation of the number of nuclei during homogeneous nucleation and nucleus growth process by CA model

Authentication

Sessions

11.Computational Science » Atomistic Structures/Microstructures/Properties/Functions

[G] Computational Materials Science

[199] Structures of subphase candidates Sm-Cu-Fe in new SmFe12-based magnets

[200] Phase equilibria of B2 Sm-Fe-Cu alloys by cluster-expansion method

[201] Development of machine learning potential for paramagnetic fcc iron

[202] Prediction of crystal structures under pressure using machine learning potentials

[203] Kinetic Monte Carlo analysis on hydrogen trapping by vacancies in B2-type PdCu alloys

[204] Quantitative phase-field modeling of interface motion with non-equilibrium solute partitioning

[205] Time variation of the number of nuclei during homogeneous nucleation and nucleus growth process by CA model

Authentication

[199] Structures of subphase candidates Sm-Cu-Fe in new SmFe₁₂-based magnets