3.021J / 1.021J / 10.333J / 18.361J / 22.00J Introduction to Modeling...
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3.021J / 1.021J / 10.333J / 18.361J / 22.00J Introduction to Modeling and Simulation Markus Buehler, Spring 2008
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1.021/3.021/10.333/18.361/22.00 Introduction to Modeling and Simulation
Part II - lecture 7
Atomistic and molecular methods
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Content overviewLectures 2-10February/March
Lectures 11-19March/April
Lectures 20-27April/May
I. Continuum methods1. Discrete modeling of simple physical systems:
Equilibrium, Dynamic, Eigenvalue problems2. Continuum modeling approaches, Weighted residual (Galerkin) methods,
Variational formulations3. Linear elasticity: Review of basic equations,
Weak formulation: the principle of virtual work, Numerical discretization: the finite element method
II. Atomistic and molecular methods1. Introduction to molecular dynamics2. Basic statistical mechanics, molecular dynamics, Monte Carlo3. Interatomic potentials4. Visualization, examples5. Thermodynamics as bridge between the scales6. Mechanical properties – how things fail7. Multi-scale modeling8. Biological systems (simulation in biophysics) – how proteins work and
how to model them
III. Quantum mechanical methods1. It’s A Quantum World: The Theory of Quantum Mechanics2. Quantum Mechanics: Practice Makes Perfect3. The Many-Body Problem: From Many-Body to Single-Particle4. Quantum modeling of materials5. From Atoms to Solids6. Basic properties of materials7. Advanced properties of materials8. What else can we do?
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Overview: Material covered Lecture 1: Introduction to atomistic modeling (multi-scale modeling paradigm, difference between continuum and atomistic approach, case study: diffusion)
Lecture 2: Basic statistical mechanics (property calculation: microscopic states vs. macroscopic properties, ensembles, probability density and partition function, solution techniques: Monte Carlo and molecular dynamics)
Lecture 3: Basic molecular dynamics (advanced property calculation, chemical interactions)
Lecture 4: Interatomic potential and force field (pair potentials, fitting procedure, force calculation, multi-body potentials-metals/EAM & applications, neighbor lists, periodic BCs, how to apply BCs)
Lecture 5: Interatomic potential and force field (cont’d) (organic force fields, bond order force fields-chemical reactions, additional algorithms (NVT, NPT), application: mechanical properties –basic introduction)
Lecture 6: Application to mechanics of materials-brittle materials (significance of fractures/flaws, brittle versus ductile behavior [motivating example], basic deformation mechanisms in brittle fracture, theory, case study: supersonic fracture (example for model building); case study: fracture of silicon (hybrid model), modeling approaches: brittle-pair potential/ReaxF, applied to silicon
Lecture 7: Application to mechanics of materials-ductile materials (dislocation mechanisms), case study: failure of copper nanocrystal, supercomputing/parallelization
Lecture 8: Review session
Lecture 9: QUIZ
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II. Atomistic and molecular methods
Lecture 7: Application to mechanics of materials-ductile materials
Outline:1. Review: brittle fracture mechanics & atomistic modeling of brittle
fracture1.1 Brittle fracture – supersonic and subsonic cracking
2. Multi-paradigm modeling of brittle fracture in silicon 3. Basic deformation mechanism in ductile materials: dislocations
3.1 Atomistic modeling studies of dislocation plasticity4. Supercomputing and parallelization
Goal of today’s lecture: Review main concepts of brittle fracture, application to chemically complex material – silicon Discuss advanced molecular dynamics simulation methods (multi-paradigm modeling)Learn basics in mechanics of ductile materials, focused on dislocations, review atomistic modeling approaches for ductile materials
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1. Review: Ductile versus brittle materials
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Tensile test of a wire: 2 types of material responses
Brittle Ductile
Strain
Stre
ss
BrittleDuctile
Necking
Figures by MIT OpenCourseWare.
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Ductile versus brittle materials
Difficultto deform,breaks easily
Easy to deformhard to break
BRITTLE DUCTILE
Glass Polymers Ice...
Shear load
Copper, Gold
Figure by MIT OpenCourseWare.
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Deformation of materials:Nothing is perfect, and flaws or cracks matter
Any material has imperfections – here shown as elliptical inclusions
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Significance of material flaws
Image removed due to copyright restrictions. Please see Fig. 1.3 in: Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
Stress concentrators: local stress >> global stress
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“Macro, global”
“Micro (nano), local”
)(rσ r
Deformation of materials:Nothing is perfect, and flaws or cracks matter
Griffith, Irwine and others: Failure initiates at defects, such as cracks, or grain boundaries with reduced traction, nano-voids, other imperfections
Failure of materials initiates at cracks
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Crack extension: brittle response
Large stresses lead to rupture of chemicalbonds between atoms
Thus, crack extends
Image removed due to copyright restrictions. Please see: Fig. 1.4 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
Figure by MIT OpenCourseWare.
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Lattice shearing: ductile response
Instead of crack extension, induce shearing of atomic latticeDue to large shear stresses at crack tipLecture 7
Figure by MIT OpenCourseWare.
Figure by MIT OpenCourseWare.
τ
τ
τ
τ
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1.1 Brittle fracture – supersonic and subsonic cracking
Focus on two aspects:1. Basic physical aspects of fracture initiation
(dissipation of elastic energy)2. Crack limiting speed, once the crack begins to
propagate
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Basic fracture process: dissipation of elastic energy
Undeformed Stretching=store elastic energy Release elastic energydissipated into breaking chemical bonds
Image removed due to copyright restrictions. Please see: Fig. 6.5 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Limiting speeds of cracks
• Under presence of hyperelastic effects, cracks can exceed the conventional barrier given by the wave speeds• This is a “local” effect due to enhancement of energy flux• Subsonic fracture due to local softening, that is, reduction of energy flux
Images removed due to copyright restrictions. Please see: Fig. 6.56 and 6.90 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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How to build a “simple” atomistic model of fracture
Must be able to capture the process of storing elastic energy
Must be able to capture the process of breaking bonds
The simple harmonic potential & harmonic bond snapping potential are the simplest representations of such a model
Undeformed Stretching=store elastic energy Release elastic energydissipated into breaking chemical bonds
weak layer=fracture plane
Figure by MIT OpenCourseWare.
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A “simple” atomistic model: geometry2
00 )(21 rrk −=φ
⎪⎪⎩
⎪⎪⎨
⎧
≥−
<−=
break2
0break0
break2
00
)(21
)(21
rrrrk
rrrrkφ
9165.012246.10
==
ρrEQ distance & density
X
YV
31/2rora
Iy
Ix
Weak fracture layer
bond can
y (store energy) 2D triangular (hexagonal) lattice
break
elasticit
stable configuration of pair potential
Figure by MIT OpenCourseWare.
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How to calculate elastic properties and wave speeds – triangular lattice, pair potential φ
12246.10 =r
EQ distance & density (same in pset 2)
''φ=k 0r
**2****rbreak0 /][/][][],,[ TLcLEkELrrr ==== φ
3**3** /][/][ LMLEE == ρ :::
*
*
*
MEL reference length (1 Å)
reference energy (347 kJ/mole)
reference mass (12 amu)
Example
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Harmonic and harmonic bond snapping potential
200 )(
21 rrk −=φ
⎪⎪⎩
⎪⎪⎨
⎧
≥−
<−=
break2
0break0
break2
00
)(21
)(21
rrrrk
rrrrkφ
Image removed due to copyright restrictions. Please see: Fig. 4.6 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Hyperelasticity or nonlinear elasticity
Image removed due to copyright restrictions. Please see: Fig. 3.10 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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MD model development: biharmonic potential
Polymers, rubber
Metals
• Stiffness change under deformation, with different strength
• Atomic bonds break at critical atomic separation
• Want: simple set of parameters that control these properties (as few as possible, to gain generic insight)
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Biharmonic potential – control parameters
breakε
0k
1k
01ratio / kkk =
breakronr r 0
0
rrr −
=ε
'φstiffening
softening
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Physical basis for subsonic/supersonic fracture
Changes in energy flow at the crack tip due to changes in local wave speed (energy flux higher in materials with higher wave speed
Image removed due to copyright restrictions. Please see: Fig. 6.38 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Supersonic fracture: mode II (shear)
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Experimental verificationIntersonic mode I fracture
Recent experiment has verified existence of intersonic mode I cracks in stiffening material (rubber)Possible explanation: Hyperelasticity or nonlinear elasticity
Theory/MD experiment
Image removed due to copyright restrictions.Please see Fig. 2 in Petersan, Paul J., Robert D. Deegan, M. Marder, and Harry L. Swinney. "Cracks in Rubber under Tension Exceed the Shear Wave Speed." Phys Rev Lett 93 (2004): 015504.
Image removed due to copyright restrictions. Please see: Fig. 9 in Buehler, Markus, and Huajian Gao. "Modeling Dynamic Fracture Using Large-Scale Atomistic Simulations." Chapter 1 in Shukla, Arun. Dynamic Fracture Mechanics. Hackensack, NJ: World Scientific, 2006.
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2. Multi-paradigm modeling of brittle fracture in silicon
Focus: model particular fracture properties of silicon (chemically complex material)
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Fracture of silicon: problem statement
Pair potential insufficientto describe bond breaking(chemical complexity)
Image courtesy of NASA.
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Concept: concurrent multi-paradigm simulations
ReaxFF
FE (c
ontin
uum
)
Organic phase
Inorganic phase
nonreactiveatomistic
nonreactiveatomistic
• Multi-paradigm approach: combine different computational methods (different resolution, accuracy, different numerical requirements..) in a single computational domain
• Decomposition of domainbased on suitability of different approaches
• Example: concurrent FE-atomistic-ReaxFF scheme in a crack problem (crack tip treated by ReaxFF) and an interface problem (interface treated by ReaxFF)
Interfaces (oxidation, grain boundaries,..)Sites of chemical reactions
Crack tips, defects (dislocations)
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Concurrent multi-paradigm simulations:link nanoscale to macroscale
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Multi-paradigm concept for fracture
Need method“good” for elastic properties
Need method“good” for describing rupture of chemical bonds
Image removed due to copyright restrictions. Please see: Fig. 1.4 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
Figure by MIT OpenCourseWare.
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Simulation geometry: fracture of silicon
• Consider a crack in a silicon crystal under mode I loading.
• Periodic boundary conditions in the z direction (corresponding to a plane strain case).
Buehler et al., Phys. Rev. Lett., 2006, 2007
Tersoff potential: Good for modeling elasticity of silicon
ReaxFF potential: Good for modeling break of bonds
Image removed due to copyright restrictions.
Please see: Fig. 2 in Buehler, Markus J., et al. "Multiparadigm Modeling of Dynamical Crack Propagation in Silicon Using a Reactive Force Field."Physical Review Letters 96 (2006): 095505. orFig. 6.95 in Buehler, Markus J. Atomistic Modeling of Materials Failure.New York, NY: Springer, 2008.
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Hybrid Hamiltonians
TersoffReaxFFTersoffReaxFF −++= UUUUtot
transition region
xxUF tot
∂∂
−=)(
Weights = describe how mucha particular FF counts (assigned to each atom)
To obtain forces:
Approach: handshaking via mixed Hamiltonians
Image removed due to copyright restrictions. Please see: Fig. 1 in Buehler, Markus J., et al. "Multiparadigm Modeling of Dynamical Crack Propagation in Silicon Using a Reactive Force Field."Physical Review Letters 96 (2006): 095505.
.
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Assigning weights to atoms
Percentage ReaxFFPercentage Tersoff(relative contribution to total energy)
100% … 100% 70% 30% 0% … 0%
0% … 0% 30% 70% 100% … 100%
Image removed due to copyright restrictions. Please see: Fig. 1 in Buehler, Markus J., et al. "Multiparadigm Modeling of Dynamical Crack Propagation in Silicon Using a Reactive Force Field."Physical Review Letters 96 (2006): 095505.
.
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TersoffReaxFFTersoffReaxFF −++= UUUUtot
TersoffReaxFFReaxFFReaxFFTersoffReaxFF )1()( UwUxwU −+=−
( ) ( )⎥⎦⎤
⎢⎣⎡ −
∂∂
−−+−=− TersoffReaxFFReaxFF
TersoffReaxFFReaxFFReaxFFTersoffReaxFF )1()( UUx
wFwFxwF
wReaxFF is the weight of the reactive force field in the handshaking region.
Hybrid Hamiltonians – force calculation
D. Sen and M. Buehler, Int. J. Multiscale Comput. Engrg., 2007
xU
F∂
∂−=Recall:
Need potential energy for force calculation )(rUtot )(xUtot xxUF tot
∂∂
−=)(
Image removed due to copyright restrictions. Please see
:
Fig. 1 in Buehler, Markus J., et al. "Multiparadigm Modeling of Dynamical Crack Propagation in Silicon Using a Reactive Force Field."Physical Review Letters 96 (2006): 095505.
xxwxw ∀=+ 1)()( TersoffReaxFF
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( ) ( )⎥⎦⎤
⎢⎣⎡ −
∂∂
−−+−=− TersoffReaxFFReaxFF
TersoffReaxFFReaxFFReaxFFTersoffReaxFF )1()( UUx
wFwFxwF
Slowly varying weights (wide transition region):
If (i.e., both force fields have similar energy landscape)
0/ReaxFF ≈∂∂ xw
0TersoffReaxFF ≈−UU
Hybrid Hamiltonians – force calculation
( )TersoffReaxFFReaxFFReaxFFTersoffReaxFF )1()( FwFxwF −+=− xxwxw ∀=+ 1)()( TersoffReaxFF
≈0
D. Sen and M. Buehler, Int. J. Multiscale Comput. Engrg., 2007
≈0
Simplified result: can interpolate forces from one end to the other
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Energy landscape of two force fields
• Schematic showing the coupling of reactive and nonreactive potentials
• At small deviations, energy landscape is identical in nonreactive and reactive modelsU
x
0EAMReaxFF ≈−UU
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Summary: mixed Hamiltonian approach
( )TersoffReaxFFReaxFFReaxFFTersoffReaxFF )1()( FwFxwF −+=−
xxwxw ∀=+ 1)()( TersoffReaxFF
Image removed due to copyright restrictions. Please see: Fig. 1 in Buehler, Markus J., et al. "Multiparadigm Modeling of Dynamical Crack Propagation in Silicon Using a Reactive Force Field."Physical Review Letters 96 (2006): 095505.
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Use multi-paradigm scheme that combines the Tersoff potential and ReaxFF
Reactive region (red) is moving with crack tip
Fracture of silicon single crystals
Image removed due to copyright restrictions.
Please see: Fig. 4a in Buehler, Markus J., et al. "Multiparadigm Modeling of Dynamical Crack Propagation in Silicon Using a Reactive Force Field."Physical Review Letters 96 (2006): 095505.or
Fig. 6.97 in Buehler, Markus J. Atomistic Modeling of Materials Failure.New York, NY: Springer, 2008.
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Cracking in Silicon: Hybrid model versusTersoff based model
Illustrates: Pure Tersoff can not describe correct crack dynamics
Image removed due to copyright restrictions.
Please see: Fig. 3a,b in Buehler, Markus J., et al. "Multiparadigm Modeling of Dynamical Crack Propagation in Silicon Using a Reactive Force Field."Physical Review Letters 96 (2006): 095505.
or
Fig. 6.96 in Buehler, Markus J. Atomistic Modeling of Materials Failure .New York, NY: Springer, 2008.
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Quantitative comparison w/ experiment
Image removed due to copyright restrictions. Please see: Fig. 1c inBuehler, M., et al. "Threshold Crack Speed Controls Dynamical Fracture of Silicon Single Crystals." Physical Review Letters 99 (2007): 165502.orFig. 6.99b in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Crack dynamics
Image removed due to copyright restrictions. Please see: Fig. 2 inBuehler, M., et al. "Threshold Crack Speed Controls Dynamical Fracture of Silicon Single Crystals." Physical Review Letters 99 (2007): 165502.orFig. 6.102 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Atomistic fracture mechanism
M.J. Buehler et al., Phys. Rev. Lett., 2007
Image removed due to copyright restrictions. Please see: Fig. 3 inBuehler, M., et al. "Threshold Crack Speed Controls Dynamical Fracture of Silicon Single Crystals." Physical Review Letters 99 (2007): 165502.
orFig. 6.104 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Fracture initiation and instabilities: movie
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Shear (mode II) loading:Crack branching
Tensile (mode I) loading:Straight cracking
Fracture mechanism: tensile vs. shear loading
Image removed due to copyright restrictions. Please see: Fig. 6.106 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Shear (mode II) loading: Crack branchingTensile (mode I) loading: Straight cracking
Fracture mechanism: tensile vs. shear loading
Mode I Mode II
Images removed due to copyright restrictions.
Please see figures in Buehler, M.J., A. Cohen, and D. Sen. “Multi-paradigm modeling of fracture of a silicon single crystal under mode II shear loading.” Journal
of Algorithms and Computational Technology 2 (2008): 203-221.
Image removed due to copyright restrictions. Please see: Fig. 6.106 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Summary: main concept of this section
Can combine different force fields in a single computational domain = multi-paradigm modeling
Enables one to combine the strengths of different force fields
Simple approach by interpolating force contributions from individual force fields, use of weights (sum of weights = 1 at all points)
ReaxFF based models quite successful, e.g. for describing fracture in silicon, quantitative agreement with experimental results
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3. Basic deformation mechanism in ductile materials: dislocations
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Significance of material flaws
Image removed due to copyright restrictions. Please see Fig. 1.3 in: Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
Stress concentrators: local stress >> global stress
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Crack extension: brittle response
Large stresses lead to rupture of chemicalbonds between atoms
Thus, crack extends
Image removed due to copyright restrictions. Please see: Fig. 1.4 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
Figure by MIT OpenCourseWare.
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Lattice shearing: ductile response
Instead of crack extension, induce shearing of atomic latticeDue to large shear stresses at crack tipLecture 7
Figure by MIT OpenCourseWare.
Figure by MIT OpenCourseWare.
τ
τ
τ
τ
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Driving forces for ductile failure: shear stresses
Images removed due to copyright restrictions. Please see: Fig. 6.30 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Hoop or opening stress
Maximum principal stress
1.5
1
1σ
0.5
00 50 100 150
θ
v/cr = 0
0.2σ xx
0.4
0.6v/cr = 0
0
0 50θ
100 150
Continuum theoryMD modeling
σ XY
v/cr = 0
0-0.2
-0.1
0.1
0.2
0
50θ
100 150
0.2σ yy
0.4
0.6
v/cr = 0
0
0 50θ
100 150
σ θ
0.2
0.4
0.6
0
0 50 100 150θ
v/cr = 0
Figures by MIT OpenCourseWare.
Angular distribution
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Perfect crystal: deformation must be cooperative movement of all atoms; the critical shear stress for this mechanism was calculated by Frenkel(1926), 1..2 GPa (μ = 50 GPa for copper):
However: shear strength of crystals measured in experiment is much lower, 100..200 MPa:
Difference explained by existence of dislocations by Orowan, Polanyi and Taylor in 1934
Confirmed by experiments with whiskers (defect free crystals that are sheared cooperatively)
μτ th ≈30
Figure by MIT OpenCourseWare.
μτ exp =100...1000
Theoretical shear strength and concept of dislocations
Figure by MIT OpenCourseWare.
τ
τ
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Concept of dislocations
Localization of shear rather than homogeneous shear that requires cooperative motion
“size of single dislocation” = b, Burgers vector 54
additional half plane
Figure by MIT OpenCourseWare.
τ
τ
τ
τ
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Animation: Dislocation motion
http://www.tf.uni-kiel.de/matwis/amat/def_en/kap_5/illustr/a5_1_1.html
Courtesy of Dr. Helmut Foell. Used with permission.
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3.1 Atomistic modeling studies of dislocation plasticity
Typically use LJ potentialor EAM potential, parameterized for metals
Yields ductile material response
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Bending a paper clip: deforming copper
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A closer look: surface cracks
http://www2.ijs.si/~goran/sd96/e6sem1y.gif
Courtesy of Goran Drazic. Used with permission.
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Case study: Crack in a copper crystal…
Do not observe crack extension! Rather, shear of latticeCreation of dislocations
Copper
Figure by MIT OpenCourseWare.
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Atomistic details of dislocation nucleation
• Dislocation nucleation from a traction-free grain boundary in an ultra thin copper film
• Atomistic results depict mechanism of nucleation of partial dislocation
[111]
[112]
stretch 10x
Figure removed for copyright reasons.
See figure 16 in Buehler, Markus J., John Balk, Eduard Arzt, and Huajian Gao. "Constrained Grain Boundary Diffusion in Thin Copper Films." Chapter 13 in Handbook of Theoretical and Computational Nanotechnology. Edited by Michael Rieth and Wolfram
Schommers. Stevenson Ranch, CA: American Scientific Publishers, 2006.or
Fig. 8.27 in Buehler, Markus J. Atomistic Modeling of Materials Failure. New York, NY: Springer, 2008.
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Dislocations in TEM
Balk, Dehm, Arzt, 2003 Courtesy of Elsevier, Inc., http://www.sciencedirect.com. Used with permission.
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Case study: plasticity in a micrometer crystal of copper
Image removed for copyright reasons.
See fig. 4 at http://tinyurl.com/nbhev6
(1 1 0)
[1 1 0]
[1 1 0] Crack faces
Mode 1 tensile loading
Y
Z
X
Figure by MIT OpenCourseWare. After Buehler et al., 2005.
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Simulation details
- 1,000,000,000 atoms
- Lennard-Jones ductile material, for copper
- Visualization using energy filtering method (only show high energy atoms)
φ
r
Genericfeatures of atomicbonding: „repulsion vs. attraction“
Case study: plasticity in a micrometer crystal of copper
(1 1 0)
[1 1 0]
[1 1 0] Crack faces
Mode 1 tensile loading
Y
Z
X
Figures by MIT OpenCourseWare. After Buehler et al., 2005.
[001]
Crack Direction [1 1 0]
y = [100]
z = [001]x = [110]
[010]
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A simulation with 1,000,000,000 particles
Image removed due to copyright restrictions.Please see: Fig. 1 in Abraham, Farid F., et al. "Simulating Materials Failure by Using up to One BillionAtoms and the World's Fastest Computer: Work-hardening." PNAS 99 (April 30, 2002): 5783-5787.
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Analysis of a one-billion atom simulation of work-hardening
Image removed due to copyright restrictions.Please see: Fig. 1c in Buehler, Markus J., et al. "The Dynamical Complexity of Work-hardening: ALarge-scale Molecular Dynamics Simulation." Acta Mechanica Sinica 21 (2005): 103-111.
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Lattice around dislocation
Atoms with higher energy than bulk are highlighted
[121]
[111]
b
Geometry of dislocation in atomic lattice
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Hardening mechanismscreation of sessile structure – makes material brittle
(Hull & Bacon)
ImPl "
age removed due to copyright restrictions. ease see "Precipitation Hardening,
http://www.bss.phy.cam.ac.uk/~amd3/teaching/A_Donald/Crystalline_solids_2.htm Image removed due to copyright restrictions. Please see:
Fig. 4 in Buehler, M., et al. "The Dynamical Complexity of Work-Hardening: A Large-Scale Molecular Dynamics Simulation."
Acta Mechanica Sinica 21 (2005): 103-111.
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Cross-slip
Activation of secondary slip systems by cross-slip and Frank-Read mechanisms: At later stages of the simulation• After activation of secondary slip systems: More dislocation reactions (e.g. cutting processes).
• Fleischer’s mechanism of cross-slip of partials that was proposed 1959
b xz
(111)
(111)[101]
w a
b
c
d
B
D
C
A
y
Hardening mechanismscreation of sessile structure – makes material brittle
Image removed due to copyright restrictions.Please see: Fig. 5b in Buehler, Markus J., et al. "The DynamicalComplexity of Work-hardening: A Large-scale Molecular DynamicsSimulation." Acta Mechanica Sinica 21 (2005): 103-111.
Figure by MIT OpenCourseWare.
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• At critical dislocation density, secondary slip systems are activated
• This enables for additional plasticity to occur, but also further contributes to work-hardening as the dislocation density increases making it more difficult for dislocations to move
Hardening mechanismscreation of sessile structure – makes material brittle
Images removed due to copyright restrictions.Please see: Fig. 5c,d in Buehler, Markus J., et al. "The DynamicalComplexity of Work-hardening: A Large-scale Molecular DynamicsSimulation." Acta Mechanica Sinica 21 (2005): 103-111.
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Formation of Lomer-Cottrell locks
• Formation of sessile Lomer-Cottrell locks, with its typical shape of a straight sessile arm connected to two partial dislocations
• Sessile junctions provide a severe burden for further dislocation glide
Hardening mechanismscreation of sessile structure – makes material brittle
Images removed due to copyright restrictions.Please see: Fig. 5e,f in Buehler, Markus J., et al. "The DynamicalComplexity of Work-hardening: A Large-scale Molecular DynamicsSimulation." Acta Mechanica Sinica 21 (2005): 103-111.
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Final sessile structure – “brittle”
Consists of:Vacancy tubes, interstitials, partial dislocations, and sessile dislocations
The more defects, the more difficult for new dislocations to pass
Makes material brittle (increased likelihood of crack extension rather than dislocation nucleation)
Images removed due to copyright restrictions.Please see: Fig. 6a in Buehler, Markus J., et al. "The DynamicalComplexity of Work-hardening: A Large-scale Molecular DynamicsSimulation." Acta Mechanica Sinica 21 (2005): 103-111.
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Final sessile structure – “brittle”
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Final sessile structure – “brittle”
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4. Supercomputing and parallelization
How to solve the numerical problem of integrating the equations of motions in MD efficiently
Use multiple computers (CPUs) to solve the problemIndividual computers can communicate results via
network
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Parallel computing – “supercomputers”
Supercomputers consist of a very large number of individual computing units (e.g. Central Processing Units, CPUs)
Images removed due to copyright restrictions
Photos of supercomputers.
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Domain decomposition
Each piece worked on by one of the computers in the supercomputer
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• Each CPU is responsible for part of the problem
• Atoms can move into other CPUs (migration)
Parallel molecular dynamics: domain decomposition
(after Schiotz)
Concept:
Divide the workload
No (immediate) long range interaction
physical simulation domain
Figure by MIT OpenCourseWare.
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Implementation of parallelization
Shared memory systems (all CPUs “see” same memory)OpenMP (easy to implement, allows incremental parallelization)POSIX threads
Distributed memory systemsMPI (=Message Passing Interface)Most widely accepted and used, very portable, but need to parallelize whole code at once
Parallelization can be very tedious and time-consuming and may distract from solving the actual problem; debugging difficult
Challenges: Load balancing, different platforms, input/output, compilers and libraries, modifications and updates to codes, “think parallel” as manager
Strategy for your own code: Find similar code and implement your own problem
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How to measure the speed of a supercomputer
Measured in “Floating point operations per second” FLOPS
Performance
MFLOPS 106, Million
109, Billion (reached in 1990s)
1012, Trillion (reached around 2000)
1015, Quadrillion (estimated to be reached in 2010)
Explanation of the different measures of computing power, and list when this power became available. In comparison a state-of-the art PC provides aperformance of 30 GFLOPS.
GFLOPS
TFLOPS
PFLOPS
Floating point operations per second (FLOPS)
Figure by MIT OpenCourseWare.
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The largest supercomputers
Figure removed due to copyright restrictions.
Chart showing what organizations possess the world’s largest supercomputers.
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Performance history
2 5
6
8
9
/L ( ) ( )
( )
10 atoms 10 atoms 10 atoms
10 atoms
10 atoms
1011 atoms
"Teraflop"
1965 1975 1985 1995 2005 2012 Year
Computer power BlueGene USA 70 TFLOP NASA Ames USA 50 TFLOP Earth Simulator Japan 40 TFLOP LINUX Clusters
IBM Almaden Spark
"Gigaflop"
"Petaflop" computers
Figure by MIT OpenCourseWare.
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Bridging length scales by direct numerical simulation (DNS)
Understand the behavior of complex many-particle systems, without imposing constraints or boundary conditions
Discover new physical phenomena, e.g. collective events that involve a large number of particles
Caution!
Need to make sure that model produces useful results, i.e. includes new scientific content and discoveries
Pictures may be pretty, but what do we learn?
Why is large-scale modeling useful?
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Visualization challenges
Huge amount of data: Single frame may have 100 GB data and moreLarge tiled display at USC, showing hypervelocity impact damage of a ceramic plate with impact velocity
Courtesy of Elsevier, Inc, http://www.sciencedirect.com. Used with permission.
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The need for “size”
Modeling of mechanical behavior of materials is highly demanding and requires models with millions and billions of atoms
200570,000,000,000
particles70 TFLOP computers
20107,000,000,000,000 particles
1,000 TFLOP computers
0.3 µm
1.2 µm
5 µm20001,000,000,000
particles10 TFLOP computers