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Analyzing Melts and Fluids from Ab Initio Molecular Dynamics Simulations with the UMD Package
Published on: September 17, 2021
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Homogeneous nucleation and microstructure evolution in million-atom molecular dynamics simulation.
Yasushi Shibuta1, Kanae Oguchi1, Tomohiro Takaki2
1Department of Materials Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
Scientific Reports
|August 28, 2015
Summary
Homogeneous nucleation in iron melts was simulated using million-atom molecular dynamics. Researchers observed spontaneous nucleation and captured microstructure evolution, advancing computational metallurgy.
Area of Science:
- Computational Materials Science
- Physical Metallurgy
- Thermodynamics
Background:
- Homogeneous nucleation is crucial for understanding solidification processes.
- Previous studies often required external factors to induce nucleation.
- Atomistic simulations offer insights into nucleation dynamics.
Purpose of the Study:
- To investigate homogeneous nucleation in undercooled iron melts using molecular dynamics.
- To analyze nucleation rate and incubation time as functions of temperature.
- To capture microstructure evolution and estimate grain growth exponent from atomistic simulations.
Main Methods:
- Utilized million-atom molecular dynamics (MD) simulations on a GPU.
- Performed 50 independent isothermal MD calculations over 1 nanosecond.
- Conducted further calculations over 10 nanoseconds for microstructure analysis.
Main Results:
- Observed characteristic temperature dependence of nucleation rate and incubation time, with a critical temperature 'nose'.
- Demonstrated spontaneous, thermally activated homogeneous nucleation without inducing factors.
- Captured atomistic details of microstructure evolution and directly estimated grain growth exponent.
Conclusions:
- MD simulations can reveal spontaneous homogeneous nucleation in undercooled melts.
- The study establishes a novel computational approach for materials science.
- Advances in computational power enable new frontiers in computational metallurgy.

