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Computational Modeling of Defects and Microstructure Dynamics in Materials under Irradiation Anter EL-AZAB Computational Science & Materials Science Programs Florida State University Collaborations Dieter Wolf (INL) Srujan Rokkam, Santosh Dubey, FSU Paul Millett, Mike Tonks, INL Support: DOE: BES-EFRC, BES-CMSN, NE-FCRD (via INL) Workshop on Characterization of Advanced Materials under Extreme Environments for Next Generation Energy Systems, Brookhaven National Laboratory, September 25-26, 2009
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Page 1: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Computational Modeling of Defects and Microstructure Dynamics in

Materials under Irradiation Anter EL-AZAB

Computational Science & Materials Science ProgramsFlorida State University

CollaborationsDieter Wolf (INL)

Srujan Rokkam, Santosh Dubey, FSUPaul Millett, Mike Tonks, INL

Support:DOE: BES-EFRC, BES-CMSN, NE-FCRD (via INL)

Workshop on Characterization of Advanced Materials under Extreme Environments for Next Generation Energy Systems, Brookhaven National Laboratory, September

25-26, 2009

Page 2: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Motivation

Irradiation damage results in complex processes of microstructural and compositional changes in materials

These processes are all driven by production, diffusion and reactions of point defects

Classical modeling approaches (e.g., clustering and nucleation theory, rate theory) are not adequate

Page 3: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void formation

Caused by vacancy super-saturation

It can be homogeneous or heterogeneous

Shape depends on crystal type

Void lattice is possible

Coupling with stress and compositional changes

In the presence of gas atoms, voids turn into gas bubbles

Irradiation-induced voids in (a) steel, (b) aluminum and (c) & (d)

magnesium

Page 4: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Research objective

Develop a unified mesoscale model to predict the concurrentmicrostructural and compositional changes in irradiated materials

Mesoscale resolve space

Concurrent processes are all driven by point defects generated by irradiation

Materials systems under consideration:

• Pure metals• Metallic alloys• Oxides

without and with gas in the matrix

Page 5: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Why the mesoscale?

Breakthroughs in understanding and predicting materials performance can be made through success at the mesoscale because this is where the materials complexity reveals itself; the mesoscale materials models fold the fundamental materials properties with the microstructural complexity to both predict and understand the macroscopic response of materials …

Page 6: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Approach

Non-equilibrium thermodynamics

Field theory of defects and microstructure phase field theory

Statistical physics underpinning

Page 7: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Typical phase-field modelsA typical phase field model is developed in two steps:

Construct a free energy functional of the system

Derive kinetic equations following Onsager formalism of non-

equilibrium T.D.

[ , ] ( , ) F c f c dη ηΩ

= Ω∫

( ),c FM tt c

δ ξδ

∂= ∇ ⋅ ∇ +

∂x ( ),FL t

tη δ ζ

δη∂

= − +∂

x

Cahn-Hilliard Eq. Allen-Cahn (G.L.) Eq.

Page 8: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Conservation properties

For a system decaying towards a lower energy state, the last kinetic equations satisfy two conditions:

Free energy decay (irreversibility)

Mass conservation

[ , ] ( , ) 0d dF c f c ddt dt

η ηΩ

= Ω ≤∫

[ , ] ( , ) 0d dM c m c ddt dt

η ηΩ

= Ω =∫

Page 9: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Conservation properties under irradiation

Irradiated materials are driven systems; irradiation deposits energy and “mass” into the system

Free energy is not necessarily decreasing with time …

Mass is not necessarily constant …

Mass conserved order parameters (defects or actual atoms)

[ , ] ( , ) ?d dF c f c ddt dt

η ηΩ

= Ω∫

[ , ] ( , ) ?d dM c m c ddt dt

η ηΩ

= Ω∫

Page 10: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Phase-field model for irradiated materials

Follow same steps without irradiation and add sources to

account for generation and reactions.

[ , ] ( , ) F c f c dη ηΩ

= Ω∫( ), ( , ) ( , )c FM t G t R t

t cδ ξδ

∂= ∇ ⋅ ∇ + + −

∂x x x

( ) ( ), ,IrradFL t t

tη δ ζ ζ

δη∂

= − + +∂

x x

modified Cahn-Hilliard Eq.

modified Allen-Cahn (G.L.) Eq.

no irradiation

This is formally equivalent to replacing F (c,η) with a Lyapunov functional J (c,η) and using the latter to derive governing eqns.

Page 11: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

2 2

[ , ] ( )

)

mv o v

v

v v

elastic

F c f c

w(c ,η

c

f d

η

η

κ κ η

Ω

⎡= ⎣

+

+ ∇ + ∇

⎤+ Ω⎦

Example: void formation due to vacancy supersaturation

Energy of a matrix with point defects

Landau energy term (bi-stability: matrix phase versus void phase)

Gradient terms due to field inhomogeneity

Stress-defect interaction energy

Page 12: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Point defect energy in matrix

mof

cv

vf

v cNE

[ ] log( ) (1 ) log(1 )B v v v vN k T c c c c+ − −eqvc

Enthalpic + Entropic energy terms

[ ] log( ) (1 )log(1 )m fo v v B v v v vf N E c N k T c c c c= + + − −

Page 13: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Energy landscape for matrix with vacancies

void

matrix with thermal equilibrium concentration

Page 14: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Numerical tests

• Void growth and shrinkage (Gibbs-Thompson Effect)

• Interaction between voids (Ostwald ripening)

• Nucleation of voids (homogeneous)

• Nucleation in the vicinity of pre-existing void

Page 15: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void growth and shrinkage

Growth and shrinkage take place depending the background concentration and the void radius

Gibbs-Thompson Effect

Page 16: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void growth and shrinkage

growth shrinkage

Page 17: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void-void interaction

Interaction between two voids surrounded by unsaturated matrix, r1=5, r2 = 10

0

1

t = 0 8 20

Ostwald ripening example

Large voids grow at the

expense of small ones

Page 18: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Homogeneous nucleation of voids under vacancy generation

Vacancy field evolution showing void nucleation due to radiation induced vacancies

t = 0 165 190 250

Voids nucleate due to fluctuations in the vacancy concentration field. The nucleation process is homogeneous

Page 19: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Nucleation close to a pre-existing void

Initial void grows while new voids nucleate …

Ripening suppresses the small voids nucleating in the vicinity of the large one.

Vacancy field evolution showing void growth in the presence of radiation effects

t = 0 210 240 250

Page 20: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Analysis of nucleation and growth

0.0

0.1

0.2

0.3

0.4

0 50 100 150 200 250 300

I II III

time

void

frac

t ion

(por

osity

)

Stage II: Nucleation regime(Johnson-Mehl-Avrami Equation)

Stage I : Incubation period

( )( )3exp1 ktpp e −−=

Stage III: Growth regime(Ostwald ripening)

( )11 τtpp o +=

1073.6 ,24.0 5−×== kpe

1088.2 ,21.0 5−×== kpe

61.144 ,14185.0 == τop

51.222 ,11119.0 == τop

Page 21: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void density as a function of time

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

50 100 150 200 250

time

num

ber

o f v

oid s

Stage II: Nucleation regime

N = Jt

Stage III: Growth (Ostwald ripening)

( ) 75.01 −−= τtNN o

764.90 ,55 == τoN

34.210 ,45 == τoN

Page 22: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Role of grain boundaries

nucleation growth

denuded GB regions

Page 23: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Introducing interstitials

Page 24: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Phase field model with interstitials included

F = N h(η) f s cv,ci( ) + j(η) f v cv,ci( ) +κv

2∇cv

2 +κ i

2∇ci

2 +κη

2∇η 2⎡

⎣ ⎢ ⎤ ⎦ ⎥

V∫ dV

∂cv

∂t= ∇ ⋅ Mv∇

1N

δFδcv

⎝ ⎜

⎠ ⎟ + ξ(r, t) + Pv (r, t) − Riv (r, t) − Sv

GB (r, t)

∂ci

∂t= ∇ ⋅ Mi∇

1N

δFδci

⎝ ⎜

⎠ ⎟ + ζ (r, t) + Pi(r, t) − Riv (r, t) − Si

GB (r, t)

∂η(r, t)∂t

= −L δFδη

+ ς (r, t) + Pv,i(r, t)

Page 25: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Ω

Cascade representation

( , )vP tr

core

shell

Page 26: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Evolution of a single cascadeDiffusion and recombination of vacancies and interstitials

Page 27: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void Growth

vc vc

ic 1

0

eqi ic c

1

0

cv and ci fields for void growth in the presence of excess vacancies in the surrounding matrix. Sv = 20, Si = 1.0

Page 28: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Fields profiles during void growth

0 100

2 10-5

4 10-5

6 10-5

8 10-5

1 10-4

1.2 10-4

0 20 40 60 80 100 120

Ci(x,0)

Ci(x,50)

Ci(x,100)

Ci(x,200)

Ci(x,300)

x

0

0.2

0.4

0.6

0.8

1

0 20 40 60 80 100 120

η(x,0)η(x,50)η(x,100)η(x,200)η(x,300)

x

0

0.2

0.4

0.6

0.8

1

30 40 50 60 70 80 90 100

Cv(x,0)

Cv(x,50)

Cv(x,100)

Cv(x,200)

Cv(x,300)

x( , )vc x t ( , )ic x t ( , )x tη

Vacancy field Interstitial field Void phase field

Fields profiles at a cross‐section at the center of the simulation cell.Void growth in the presence of excess vacancies in the surrounding matrix. Sv = 20, Si = 1.0 (No radiation source)

Page 29: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void radius with supersaturation

74

74.2

74.4

74.6

74.8

75

0 10 20 30 40 50 60 70 80

Sv=0,S

i=1

Sv=1,S

i=1

Sv=2,S

i=1

Sv=3,S

i=1

Sv=5,S

i=1

Sv=10,S

i=1

Sv=0.1,S

i=1

Sv=1,S

i=2

Sv=1,S

i=5

Sv=1,S

i=50

Time (t)

Void radius as a function of time, for different initial defect supersaturation

Page 30: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void growth under irradiation

( ) 80 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 120 c t =

( ) 80 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 120 c t =

vc

ic

vc

1

0

eqi ic c

1

0

Vacancy and interstitial field evolution showing void growth in the presence of radiation effects.

Sv=50, Si = 1, Pv=0.25, Pi = 0.15 (on 128 x 128 grid)

Page 31: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Effect of thermal fluctuations on void growth under irradiation

( ) 40 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 75 c t =

( ) 40 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 75 c t =

vc

1

0

eqi ic c

1

0

vc

ic

Vacancy and interstitial field evolution showing void growth in the presence of radiation effects and thermal fluctuations.

Sv=50, Si = 1, Pv=0.25, Pi = 0.15 on 128 x 128 grid

Page 32: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void nucleation and growth due to irradiation

( ) 50 b t = ( ) 400 d t =0~ =t(a) Initial ( ) 200 c t =

( ) 50 b t = ( ) 400 d t =0~ =t(a) Initial ( ) 200 c t =

vc

ic

vc

1

0

eqi ic c

1

0

Vacancy and interstitial field evolution showing void nucleation due to radiation effects. Sv=50, Si = 1, Pv=0.25, Pi = 0.15 on 128x128 grid

Page 33: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Effect of thermal fluctuations on void nucleation and growth

( ) 50 b t = ( ) 400 d t =0~ =t(a) Initial ( ) 75 c t =

( ) 50 b t = ( ) 400 d t =0~ =t(a) Initial ( ) 75 c t =

vc

ic

vc

1

0

eqi ic c

1

0

Vacancy and interstitial field evolution showing void nucleation radiation effects and thermal fluctuations.

Sv=50, Si = 1, Pv=0.25, Pi = 0.15 on 128 x 128 grid

Page 34: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Analysis of Nucleation and Growth

0 100

5 10-2

1 10-1

1.5 10-1

2 10-1

2.5 10-1

0 100 200 300 400

Pv=0.25, P

i=0.15

Pv=0.15, P

i=0.10

Pv=0.25, P

i=0.15, ξ=0.1%

Time (t)

I II III

Stage II: Nucleation regime(Johnson‐Mehl‐AvramiEquation)

Stage I : Incubation period

( )( )3exp1 ktpp e −−=

Stage III: Growth regime(Ostwald ripening)

( )11 τtpp o +=

NOTE: The change in incubation time with decrease of cascade size and with thermal fluctuations

Page 35: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void growth under irradiation

Vacancy and interstitial field evolution showing void growth in the presence of radiation effects.

Sv=50, Si = 1, Pv=0.25, Pi = 0.15 (on 256 x 256 grid), rvoid = 10

vc

1

0

eqi ic c

1

0

( ) 100 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 200 c t =

( ) 100 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 200 c t =

vc

ic

Page 36: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Void nucleation under irradiation

vc

ic

( ) 105 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 200 c t =

vc

1

0

eqi ic c

1

0

( ) 105 b t = ( ) 300 d t =0~ =t(a) Initial ( ) 200 c t =

Vacancy and interstitial field evolution showing void nucleation presence of radiation effects.

Sv=50, Si = 1, Pv=0.25, Pi = 0.15 (on 256 x 256 grid)

Page 37: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Role of grain boundaries

Page 38: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Nucleation and growth (movies)

Page 39: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Nucleation and growth (movies)

Page 40: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Gas effects and bubble formation

host atom vacancy dumbbellself-interstitial

gas atom

The model has been extended to include gas atoms and to model the nucleation and growth of gas bubbles. Preliminary results show good agreement with experimental observations

Page 41: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

Summary

A phase field model for void/bubble nucleation and growth

Vacancies, interstitials, gas atoms represented

Models seems to predict the defect, void and bubble dynamics under irradiation

Page 42: Computational Modeling of Defects and Microstructure ... El-Azab_BNL-Workshop.pdfNumerical tests • Void growth and ... 0.8 1 0 2040 6080100120 η(x,0) η(x,50) η(x,100) η(x,200)

In progress

Current model:

Thin interface analysis to fix parameters and apply to real materialsModel dislocation loop nucleationAdd stress effects and diffusion anisotropy (capture void lattices)Anisotropic surface energy – directional dependence of gradient energy term

Generalization to multi-component systems


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