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

Byeong-Joo Lee  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  Textured Steels  Computational Design of Structural Materials  SiC Single Crystal Growth  Virtual Lab for Nano Materials Outline

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

Byeong-Joo Lee Grain Boundary Identification Scheme How to uniquely define misorientation and inclination between two neighboring grains 2NN MEAMExtensionMulti-scale GBE DB GB Identification

Byeong-Joo Lee Sigma (Σ)Theta (θ)(hkl) planeSigma (Σ)Theta (θ)(hkl) plane Grain Boundary Energy of BCC Fe Scripta Mater. (2011) 2NN MEAMExtensionMulti-scale GBE DB GB Identification

Byeong-Joo Lee Crystal structureCrystal symmetry Sample symmetry Orthotropic Φφ2φ2 φ1φ1 Cubic90° Tetragonal 90° Orthorhombic 90°180° Hexagonal 90°60° Trigonal 90°120° Monoclinic 90°360° Triclinic 180°360° Size of the Euler space necessary to uniquely represent orientations for various crystal and sample symmetry. Other crystalline structures

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

Byeong-Joo Lee Calculation of Grain Boundary Energy Calculation of Grain Boundary Energy B.-J. Lee, MSMSE (2004)

Byeong-Joo Lee Grain Boundary Energy of FCC Fe

Byeong-Joo Lee Interfacial Energy between BCC & FCC Fe

Byeong-Joo Lee Implementation of GBE DB into mesoscale Simulation Σ3 Σ9Σ9 Grain Boundary Energy as a single function of misorientation and inclination ?? Numerical Method 2NN MEAMExtension Multi-scale GBE DBGB Identification

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

Byeong-Joo Lee Effect of Alloying Elements on GB Energy 2NN MEAM Extension Multi-scale GBE DBGB Identification

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

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

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

Byeong-Joo Lee 2NN MEAM Interatomic Potentials 2NN MEAM Interatomic Potentials – for pure Elements PropertyMEAM-Al (exp.) MEAM-Fe (exp.) C 11 (10 12 dyne/cm 2 ) C 12 (10 12 dyne/cm 2 ) C 44 (10 12 dyne/cm 2 ) E v f (eV) Q D (eV) E I f (eV) (1.143) (0.619) (0.316) 0.68 (0.68) 1.33 (1.33) 2.49 (-) (2.431) (1.381) (1.219) 1.75 (1.79) 2.28 (2.5) 4.20 (-) E (100) (mJ/m 2 ) E (110) (mJ/m 2 ) E (111) (mJ/m 2 ) d (100) (%) d (110) (%) d (111) (%) 848 (1085 a ) 948 (1085 a ) 629 (1085 a ) +1.8 (+1.8) -8.9 (-8.5±1.0) +1.0 (0.9±0.5) 2510 (2360 a ) 2356 (2360 a ) 2668 (2360 a ) -1.1 (-0.2, -1.5) -1.5 (0) (-16.9) E bcc/fcc (eV/atom) E fcc/hcp (eV/atom) 0.12 (0.10 b ) 0.03 (0.06 b ) (0.082 b ) ( b ) (0-100 o C) (10 -6 /K) C p (0-100 o C) (J/mol·K) m.p. (K) H m (KJ/mol) V m (%) 22.0 (23.5) 26.2 (24.7) 937 (933) 11.0 (10.7) 6.7 (6.5) 12.4 (12.1) 26.1 (25.5) 2000 (1811) 13.2 (13.8) 4.0 (3.5)

Byeong-Joo Lee Pure Elements Fe, Cr, Mo, W, V, Nb, Ta, LiPhys. Rev. B. 64, (2001); MSMSE 20, (2012). Cu, Ag, Au, Ni, Pd, Pt, Al, PbPhys. Rev. B. 68, (2003). Ti, Zr & MgPhys. Rev. B. 74, (2006); CALPHAD 33, (2009). Mn, PActa Materialia 57, (2009).; J. Phys.: Condensed Matters (2012), in press. C, Si, Ge, In CALPHAD 29, 7-16 (2005); 31, (2007); 32, (2008); 32, (2008) Multicomponent Systems Fe-C, Fe-N, Fe-HActa Materialia 54, (2006); 54, (2006); 55, (2007). Fe-Ti & Fe-NbScripta Materialia 59, (2008). Fe-Ti-C & Fe-Ti-N Acta Materialia 56, (2008); Acta Materialia 57, (2009). Fe-Nb-C & Fe-Nb-NJ. Materials Research 25, (2010). Al-H & Ni-H, V-HJ. Materials Research 26, (2011); CALPHAD 35, (2011). Fe-MnActa Materialia 57, (2009). Fe-Cr CALPHAD 25, (2001). Fe-Cu Phys. Rev. B. 71, (2005). Fe-Pt J. Materials Research 21, (2006). Fe-Al J. Phys.: Condensed Matters 22, (2010) Fe-PJ. Phys.: Condensed Matters (2012), in press. Al-Ni CALPHAD 31, 53 (2007). Co-Cu J. Materials Research 17, (2002). Co-Pt Scripta Materialia 45, (2001). Cu-NiCALPHAD 28, (2004). Ni-WJ. Materials Research 18, (2003). Cu-TiMater. Sci. and Eng. A , 733 (2007). Cu-ZrJ. Materials Research 23, 1095 (2008). Cu-Zr-AgScripta Materialia 61, 801 (2009). Mg-Al, Mg-LiCALPHAD 33, (2009); MSMSE 20, (2012). Ga-In-N J. Phys.: Condensed Matter 21, (2009). Second Nearest Neighbor Modified EAM (2NN MEAM)

Byeong-Joo Lee Surface Bulk Concentration Surface Concentration Ave. Concentration Surface 3 layers Surface E, J/m 2 (100)1.6%68%25%0.29 (110)1.6%37%16%0.83 (111)1.6%78%27%0.38 E surf of pure Fe = 2.50, 2.35, 2.56 for (100), (110), (111) (100)0.3%66%23%0.68 (110)0.3%35%14%1.14 (111)0.3%74%25%0.78 Development of Textured Steels Change of Surface Energy Anisotropy due to Surface Segregation Change of Surface Energy Anisotropy due to Surface Segregation Surface Segregation of impurity atoms on Fe surfaces Virtual Nano Lab.SiC Crystal Growth Structural Materials textured steels

Byeong-Joo Lee Phase-Field simulations considering the surface/GB segregation kinetics of impurity atoms as well as the grain growth is an on-going research. Development of Textured Steels

Byeong-Joo Lee Virtual Nano Lab.SiC Crystal Growth Structural Materials textured steels Multiscale Computational Design of Structural Materials

Byeong-Joo Lee SiC Crystal growth simulation Effect of gas temperature substrate temperature deposition rate vapor composition doping elements, etc. on the defect formation Virtual Nano Lab. SiC Crystal Growth Structural Materials textured steels

Byeong-Joo Lee SiC Crystal growth simulation Effect of process conditions on the resultant crystal structure, 4H vs. 6H

Byeong-Joo Lee Virtual Nano Lab. SiC Crystal Growth Structural Materials textured steels Virtual Nano Lab

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

Byeong-Joo Lee 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