Homogeneous nucleation and microstructure evolution in million-atom molecular dynamics simulation

Homogeneous nucleation from an undercooled iron melt is investigated by the statistical sampling of million-atom molecular dynamics (MD) simulations performed on a graphics processing unit (GPU). Fifty independent instances of isothermal MD calculations with one million atoms in a quasi-two-dimensional cell over a nanosecond reveal that the nucleation rate and the incubation time of nucleation as functions of temperature have characteristic shapes with a nose at the critical temperature. This indicates that thermally activated homogeneous nucleation occurs spontaneously in MD simulations without any inducing factor, whereas most previous studies have employed factors such as pressure, surface effect, and continuous cooling to induce nucleation. Moreover, further calculations over ten nanoseconds capture the microstructure evolution on the order of tens of nanometers from the atomistic viewpoint and the grain growth exponent is directly estimated. Our novel approach based on the concept of “melting pots in a supercomputer” is opening a new phase in computational metallurgy with the aid of rapid advances in computational environments.

[1]  Mohsen Asle Zaeem,et al.  Quantitative Modeling of the Equilibration of Two-Phase Solid-Liquid Fe by Atomistic Simulations on Diffusive Time Scales , 2015 .

[2]  D. Frenkel,et al.  Prediction of absolute crystal-nucleation rate in hard-sphere colloids , 2001, Nature.

[3]  Y. Shibuta,et al.  A molecular dynamics study of the phase transition in bcc metal nanoparticles. , 2008, The Journal of chemical physics.

[4]  Yunzhi Wang,et al.  Grain growth in anisotropic systems: comparison of effects of energy and mobility , 2002 .

[5]  Michael P. Anderson,et al.  Computer simulation of grain growth—IV. Anisotropic grain boundary energies , 1985 .

[6]  H. C. Andersen Molecular dynamics simulations at constant pressure and/or temperature , 1980 .

[7]  W. Kurz,et al.  Fundamentals of Solidification , 1990 .

[8]  Toshio Suzuki,et al.  Phase-field model for binary alloys. , 1999, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[9]  P. S. Sahni,et al.  Computer simulation of grain growth—I. Kinetics , 1984 .

[10]  Y. Shibuta,et al.  Growth and melting of nanoparticles in liquid iron: A molecular dynamics study , 2009 .

[11]  W. Kurz,et al.  Fundamentals of Solidification: Fourth Revised Edition , 1998 .

[12]  Y. Shibuta,et al.  A Molecular Dynamics Study of the Energy and Structure of the Symmetric Tilt Boundary of Iron , 2008 .

[13]  Kanae Oguchi,et al.  Large-scale Molecular Dynamics Study on Evolution of Grain Boundary Groove of Iron , 2012 .

[14]  A. Karma,et al.  Quantitative phase-field modeling of dendritic growth in two and three dimensions , 1996 .

[15]  H. Berendsen,et al.  Molecular dynamics with coupling to an external bath , 1984 .

[16]  R. B. Potts Some generalized order-disorder transformations , 1952, Mathematical Proceedings of the Cambridge Philosophical Society.

[17]  Y. Shibuta,et al.  A Molecular Dynamics Study of Thermodynamic and Kinetic Properties of Solid-Liquid Interface for Bcc Iron , 2010 .

[18]  Mats Hillert,et al.  On the theory of normal and abnormal grain growth , 1965 .

[19]  R. Kobayashi Modeling and numerical simulations of dendritic crystal growth , 1993 .

[20]  P. S. Sahni,et al.  Grain growth in two dimensions , 1983 .

[21]  Jincheng Wang,et al.  Phase-field study of competitive dendritic growth of converging grains during directional solidification , 2012 .

[22]  Y. Shibuta,et al.  A molecular dynamics study of cooling rate during solidification of metal nanoparticles , 2011 .

[23]  Jiangwei Wang,et al.  Formation of monatomic metallic glasses through ultrafast liquid quenching , 2014, Nature.

[24]  Y. Shibuta,et al.  Million-atom molecular dynamics simulation on spontaneous evolution of anisotropy in solid nucleus during solidification of iron , 2014 .

[25]  Y. Shibuta,et al.  Accelerating Molecular Dynamics Simulation Performed on GPU , 2012 .

[26]  M. Finnis,et al.  A simple empirical N-body potential for transition metals , 1984 .

[27]  James N Glosli,et al.  Beyond finite-size scaling in solidification simulations. , 2006, Physical review letters.

[28]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[29]  Munekazu Ohno,et al.  Quantitative phase-field modeling of nonisothermal solidification in dilute multicomponent alloys with arbitrary diffusivities. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  O. Hunderi,et al.  Computer simulation of grain growth , 1979 .

[31]  Marco Berghoff,et al.  Phase-Field Simulations at the Atomic Scale in Comparison to Molecular Dynamics , 2013, TheScientificWorldJournal.

[32]  Lennart Bergström,et al.  Pre-nucleation clusters as solute precursors in crystallisation. , 2014, Chemical Society reviews.

[33]  Mark Asta,et al.  Crystal-melt interfacial free energies and mobilities in fcc and bcc Fe , 2004 .

[34]  H. Inoue,et al.  Numerical simulation of equiaxed grain formation in weld solidification , 2003 .

[35]  T. Takaki Phase-field Modeling and Simulations of Dendrite Growth , 2014 .

[36]  T. Takaki,et al.  Two-dimensional phase-field simulations of dendrite competitive growth during the directional solidification of a binary alloy bicrystal , 2014 .

[37]  Y. Shibuta,et al.  Melting and nucleation of iron nanoparticles: A molecular dynamics study , 2007 .

[38]  G. Galli,et al.  Surface-induced crystallization in supercooled tetrahedral liquids. , 2008, Nature materials.

[39]  A. Godfrey,et al.  Some Monte Carlo studies of grain growth in a temperature gradient , 1995 .

[40]  Y. Shibuta,et al.  Solidification in a Supercomputer: From Crystal Nuclei to Dendrite Assemblages , 2015 .

[41]  C. Morón,et al.  Computer simulation of grain growth kinetics , 2000 .