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  1. Computational Materials Science & Engineering Lab.Pohang University of Science & Technology Atomistic Simulations for Materials Research towarda computational materials and process design Byeong-Joo Lee

  2. Outline • Atomistic Simulation • Grain Boundary Identification Scheme • Construction of Grain Boundary Energy Database • Implementation of the DB into Mesoscale Simulations • Extension into Multicomponent system • 2NN MEAM Interatomic Potential • Application to Materials and Process Design • <100> Textured Steels • Computational Design of Structural Materials • SiC Single Crystal Growth • Virtual Lab for Nano Materials

  3. Grain Boundary/Interface Energy Wetting angle : 36o Wetting angle : 120o Fe - 0.5% Mn – 0.1% C, dT/dt = 1 oC/s from SG Kim, Kunsan University

  4. Grain Boundary Identification Scheme GB Identification GBE DB Multi-scale Extension 2NN MEAM How to uniquely define misorientation and inclination between two neighboring grains

  5. GB Identification GBE DB Multi-scale Extension 2NN MEAM Grain Boundary Energy of BCC Fe Scripta Mater. (2011)

  6. Other crystalline structures Size of the Euler space necessary to uniquely represent orientations for various crystal and sample symmetry.

  7. Conventional Method for Calculation of GB/IFC Energy σ = {E( ) – [E( )+E( )]} / 2A Mismatch in periodic length

  8. Calculation of Grain Boundary EnergyB.-J. Lee, MSMSE (2004)

  9. Grain Boundary Energy of FCC Fe

  10. Interfacial Energy between BCC & FCC Fe

  11. GB Identification GBE DB Multi-scale Extension 2NN MEAM Implementation of GBE DB into mesoscale Simulation Σ3 Σ9 Grain Boundary Energy as a single function of misorientation and inclination ?? Numerical Method

  12. Test phase field simulation of grain growth - Anisotropic GBE (realistic GBE DB) - Isotropic GBE (500 steps) (2000 steps) • Sample Size: 200*200*200 grids - Isotropic GB mobility

  13. GB Identification GBE DB Multi-scale Extension 2NN MEAM Effect of Alloying Elements on GB Energy

  14. Effect of Temperature on GB Energy (110) Symmetric Tilt Boundary Energy of pure Al Otsuki and Mizuno 1986 calculated at 0 K measured near melting point • Introduction of a simple temperature dependence • GB transition in alloy system and its effect on the GB segregation ??

  15. GB Identification GBE DB Multi-scale Extension 2NN MEAM 2NN MEAM Interatomic Potentials – History of Development • EAM Potentials (1983, M.S. Daw and M.I. Baskes) • ▷ Successful mainly for FCC elements • - many other many-body potentials show similar performance • 1NN MEAM Potentials (1987,1992, M.I. Baskes) • ▷ Show Possibility for description of various structures • - important to be able to describe multi-component system • 2NN MEAM Potentials (2000, B.-J. Lee & M.I. Baskes) • ▷ Applicable to fcc, bcc, hcp, diamond structures and their alloys

  16. Elastic Constants ▷ B, C11, C12, C44, ... Defect Energy ▷ Surface Energy ▷ Heat of Vacancy Formation, … Structural Energy ▷ Energy and Lattice Parameters in Different Structures Thermal Property ▷ Specific Heat ▷ Thermal Expansion Coefficient ▷ Melting Temperature, ... Semi-Empirical Interatomic Potentials – Basic Requirement

  17. 2NN MEAM Interatomic Potentials – for pure Elements

  18. Second Nearest Neighbor Modified EAM (2NN MEAM) • Pure Elements • Fe, Cr, Mo, W, V, Nb, Ta, Li Phys. Rev. B. 64, 184102 (2001);MSMSE 20, 035005 (2012) . • Cu, Ag, Au, Ni, Pd, Pt, Al, Pb Phys. Rev. B. 68, 144112 (2003). • Ti, Zr & Mg Phys. Rev. B. 74, 014101 (2006); CALPHAD 33, 650-57 (2009). • Mn, P Acta Materialia 57, 474-482 (2009).; J. Phys.: Condensed Matters (2012), in press. • C, Si, Ge, In CALPHAD 29, 7-16 (2005); 31, 95-104 (2007); 32, 34-42 (2008); 32, 82-88 (2008) • Multicomponent Systems • Fe-C, Fe-N, Fe-H Acta Materialia 54, 701-711 (2006); 54, 4597-4607 (2006); 55, 6779-6788 (2007). • Fe-Ti & Fe-Nb Scripta Materialia 59, 595-598 (2008). • Fe-Ti-C & Fe-Ti-N Acta Materialia 56 , 3481-3489 (2008); Acta Materialia 57 , 3140-3147 (2009). • Fe-Nb-C & Fe-Nb-N J. Materials Research 25, 1288-1297 (2010). • Al-H & Ni-H, V-H J. Materials Research 26, 1552-1560 (2011); CALPHAD 35, 302-307 (2011). • Fe-Mn Acta Materialia 57, 474-482 (2009). • Fe-Cr CALPHAD 25, 527-534 (2001). • Fe-Cu Phys. Rev. B. 71, 184205 (2005). • Fe-Pt J. Materials Research 21, 199-208 (2006). • Fe-Al J. Phys.: Condensed Matters 22, 175702 (2010) • Fe-P J. Phys.: Condensed Matters (2012), in press. • Al-Ni CALPHAD 31, 53 (2007). • Co-Cu J. Materials Research 17, 925-928 (2002). • Co-Pt Scripta Materialia 45, 495-502 (2001). • Cu-Ni CALPHAD 28, 125-132 (2004). • Ni-W J. Materials Research 18, 1863-1867 (2003). • Cu-Ti Mater. Sci. and Eng. A 449-451, 733 (2007). • Cu-Zr J. Materials Research 23, 1095 (2008). • Cu-Zr-Ag Scripta Materialia 61, 801 (2009). • Mg-Al , Mg-Li CALPHAD 33, 650-57 (2009); MSMSE 20, 035005 (2012) . • Ga-In-N J. Phys.: Condensed Matter 21, 325801 (2009). 2NN MEAM is available in Lammps

  19. <100> textured steels Structural Materials SiC Crystal Growth Virtual Nano Lab. Developmentof <100> Textured Steels • Change of Surface Energy Anisotropy due to Surface Segregation Surface Segregation of impurity atoms on Fe surfaces

  20. Developmentof <100> Textured Steels < Surface > < Bulk > Phase-Field simulations considering the surface/GB segregation kinetics of impurity atoms as well as the grain growth is an on-going research.

  21. <100> textured steels Structural Materials SiC Crystal Growth Virtual Nano Lab. Multiscale Computational Design of Structural Materials

  22. <100> textured steels Structural Materials SiC Crystal Growth Virtual Nano Lab. SiC Crystal growth simulation • Effect of • gas temperature • substrate temperature • deposition rate • vapor composition • doping elements, etc. • on the defect formation

  23. SiC Crystal growth simulation Effect of process conditions on the resultant crystal structure, 4H vs. 6H

  24. <100> textured steels Structural Materials SiC Crystal Growth Virtual Nano Lab. Virtual Nano Lab

  25. Virtual Nano Lab Virtual Lab for Li Ion Battery Materials Full Cell Simulation Lab. • Reliability Test Lab. • Phase field simulation • Tools & method • Cathode Design Lab. • Model construction • Screening • SEI reaction simulation • Structure optimization • Anode Design Lab. • Novel materials design • Intercalation reaction • SEI reaction simulation • Structure optimization • Electrolyte Design Lab. • Electrolyte Structure Optimization • Characterization of Electrolyte

  26. Summary • Fundamental materials properties are provided by • atomistic simulations based on interatomic potential • Macroscale materials properties are obtained from • multiscale simulations • Multiscale simulation is used for materials and process • design of structural materials • Atomistic simulation is used for materials and process • design of nano materials, directly or through a virtual • nano fab platform