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Nuclea'on	
  and	
  avalanches	
  	
  
in	
  films	
  with	
  labyrinthine	
  
magne'c	
  domains	
  
Andrea	
  Benassi	
  &	
  
Stefano	
  Zapperi	
  	
  
Outline	
  
Experiments	
  on	
  labyrinthine	
  domains	
  
	
  
Our	
  phase	
  field	
  model	
  
	
  
Characteris>cs	
  Lengths	
  and	
  avalanche	
  sta>s>cs	
  
	
  
	
  
	
  
A	
  new	
  version	
  of	
  the	
  phase	
  field	
  model	
  
	
  
Ironing	
  stripe	
  domains	
  
	
  
Memory	
  effects	
  	
  	
  	
  
	
  
	
  
	
  
In-­‐plane	
  magne>za>on:	
  very	
  preliminary	
  results	
  (yesterday)	
  
Labyrinthine	
  domains	
  
Phys.Rev.Le*.	
  92,	
  
077206	
  (2004)	
  	
  	
  
	
  
Phys.Rev.B	
  71,	
  
104431	
  (2005)	
  
Deconvolving	
  
nucleaAon	
  
they	
  find	
  a	
  0.5	
  
exponent	
  
Labyrinthine	
  domains	
  
Avalanche	
  staAsAcs	
  taken	
  over	
  
different	
  intervals	
  of	
  the	
  hysteresis	
  
loop	
  show	
  different	
  criAcal	
  exponents	
  
Appl.Phys.Le*.	
  95,	
  182504	
  (2009)	
  
A	
  phase	
  field	
  model	
  
V =
Ku
4

m2
2
−
m4
4

m =
M(r)
Ms
= m(x, y)
A	
  phase	
  field	
  model	
  
V =
Ku
4

m2
2
−
m4
4

m =
M(r)
Ms
= m(x, y)
∂M(r, t)
∂t
= −Γ
δH[M(r, t)]
δM(r, t)
Energy	
  funcAonal	
  power	
  expansion	
  
+	
  
linear	
  relaAon	
  between	
  Ame	
  and	
  
energy	
  fluctuaAons	
  
Small	
  Ame	
  
fluctuaAons	
  
hypothesis	
  
A	
  phase	
  field	
  model	
  
hr(r) = 0
hr(r)hr(r
) = Dδ(r − r
)
V =
Ku
4

m2
2
−
m4
4

m =
M(r)
Ms
= m(x, y)
∂M(r, t)
∂t
= −Γ
δH[M(r, t)]
δM(r, t)
Energy	
  funcAonal	
  power	
  expansion	
  
+	
  
linear	
  relaAon	
  between	
  Ame	
  and	
  
energy	
  fluctuaAons	
  
Small	
  Ame	
  
fluctuaAons	
  
hypothesis	
  
2	
  dimensionless	
  
parameters	
  
 = 2

A/Ku
α = Ku/4µ0M2
s
γ = d/4π
A	
  phase	
  field	
  model	
  
hr(r) = 0
hr(r)hr(r
) = Dδ(r − r
)
V =
Ku
4

m2
2
−
m4
4

m =
M(r)
Ms
= m(x, y)
∂M(r, t)
∂t
= −Γ
δH[M(r, t)]
δM(r, t)
Energy	
  funcAonal	
  power	
  expansion	
  
+	
  
linear	
  relaAon	
  between	
  Ame	
  and	
  
energy	
  fluctuaAons	
  
Small	
  Ame	
  
fluctuaAons	
  
hypothesis	
  
2	
  dimensionless	
  
parameters	
  
 = 2

A/Ku
α = Ku/4µ0M2
s
γ = d/4π
Two	
  different	
  limit	
  behaviors	
  
Depending	
  on	
  the	
  film	
  
thickness	
  and	
  on	
  the	
  disorder	
  
strength	
  we	
  can	
  have	
  two	
  limit	
  
behaviors	
  
-4 -2 0
-0.5
0
0.5
42
b
c
d
f a
γ = 0.5
γ = 0.6
γ = 0.7
h
e
g
b c da
f g he
Two	
  different	
  limit	
  behavors	
  
MulAple	
  nucleaAon	
  and	
  
coalescence	
  by	
  bridging	
  
Expansion	
  by	
  branching	
  of	
  a	
  single	
  
domain	
  and	
  lateral	
  fa*ening	
  	
  
Characteris'c	
  lengths	
  
m(x, y, d) = sin

πx
d

m(x, y, w) = tanh

x
w

d = α/γ domain width
w =
√
2 domain wall width
n nucleation diameter
MinimizaAon	
  of	
  the	
  energy	
  with	
  respect	
  to	
  a	
  
fixed	
  magneAzaAon	
  configuraAon	
  with	
  one	
  
parameter:	
  
NucleaAon	
  depends	
  strongly	
  on	
  disorder,	
  any	
  
analyAcal	
  theory	
  is	
  useless!!!	
  
Characteris'c	
  lengths	
  
m(x, y, d) = sin

πx
d

m(x, y, w) = tanh

x
w

d = α/γ domain width
w =
√
2 domain wall width
n nucleation diameter
MinimizaAon	
  of	
  the	
  energy	
  with	
  respect	
  to	
  a	
  
fixed	
  magneAzaAon	
  configuraAon	
  with	
  one	
  
parameter:	
  
NucleaAon	
  depends	
  strongly	
  on	
  disorder,	
  any	
  
analyAcal	
  theory	
  is	
  useless!!!	
  
Avalanches	
  
Triggering	
  of	
  minor	
  avalanches	
  
The	
  difference	
  between	
  
consecuAve	
  magneAzaAon	
  
maps	
  allows	
  a	
  direct	
  imaging	
  
of	
  avalanches	
  	
  
Avalanche	
  sta's'cs	
  
Analysis	
  of	
  different	
  loop	
  regions:	
  
	
  
•  The	
  maximum	
  avalanche	
  size	
  decreases	
  as	
  
the	
  domain	
  density	
  reaches	
  its	
  maximum	
  
•  NucleaAon	
  and	
  bridging,	
  with	
  their	
  
characterisAc	
  size,	
  affect	
  the	
  size	
  
distribuAon	
  
	
  
	
  	
  	
  
NucleaAon	
  and	
  annihilaAon:	
  	
  
	
  
•  For	
  nucleaAon	
  to	
  take	
  place	
  a	
  barrier	
  must	
  
be	
  overcame,	
  its	
  value	
  goes	
  as	
  1/γ	

•  AnnihilaAon	
  is	
  almost	
  independent	
  of	
  the	
  
dipolar	
  field	
  strength	
  
•  At	
  zero	
  temperature	
  the	
  gaussian	
  
distribuAon	
  is	
  due	
  to	
  the	
  spaAal	
  disorder	
  
Avalanche	
  sta's'cs	
  
Different	
  film	
  thickness:	
  
	
  
•  The	
  avalanche	
  cutoff	
  increases	
  when	
  γ	
  is	
  
decreased,	
  following	
  the	
  corresponding	
  
increase	
  of	
  the	
  domain	
  width	
  and	
  
confirming	
  that	
  α/γ	
  is	
  the	
  relevant	
  
parameter	
  controlling	
  the	
  size	
  of	
  the	
  
scaling	
  regime	
  
Different	
  Disorder	
  strength:	
  
	
  
•  The	
  Larger	
  D	
  the	
  larger	
  the	
  external	
  field	
  at	
  
which	
  walls	
  depin,	
  the	
  larger	
  their	
  jumps.	
  	
  
•  Increasing	
  D	
  the	
  domains	
  shape	
  is	
  slightly	
  
affected	
  by	
  the	
  disorder	
  strength	
  but	
  	
  	
  	
  	
  	
  	
  is	
  
almost	
  independent	
  of	
  D,	
  
•  NucleaAon	
  diameter	
  	
  	
  	
  	
  	
  	
  decreases	
  with	
  
increasing	
  D	
  
d = α
n nucleation diame
Phase	
  field	
  model	
  reloaded	
  
V = [1 − λ(r)]
¯Ku
4

m2
2
−
m4
4

˙m = α

dV
dm
+ ∇2
m

− γ

dr m(r
)
|r − r|3
+ hr(r) + he(t) + R(t)
hr(r) = 0 hr(r)hr(r
) = Dδ(r − r
)
Two	
  new	
  randomness	
  sources	
  means	
  two	
  new	
  physical	
  parameters	
  to	
  be	
  introduced…	
  	
  
λ(r) = 0 λ(r)λ(r
) = Aδ(r − r
)
R(r)R(r
) = 2KBTδ(r − r
)δ(t − t
)R(r) = 0
Random	
  field	
  
Temperature	
  noise	
  
Anisotropy	
  disorder	
  
Random	
  field	
  and	
  random	
  anisotropy	
  has	
  the	
  same	
  effect	
  on	
  the	
  domains	
  topography,	
  
except	
  that	
  the	
  type	
  of	
  domain	
  dynamics	
  (nucleaAon/coalescence	
  or	
  branching)	
  seems	
  to	
  
be	
  a	
  bit	
  more	
  sensiAve	
  to	
  A	
  than	
  D.	
  
Phase	
  field	
  model	
  reloaded	
  
V = [1 − λ(r)]
¯Ku
4

m2
2
−
m4
4

˙m = α

dV
dm
+ ∇2
m

− γ

dr m(r
)
|r − r|3
+ hr(r) + he(t) + R(t)
hr(r) = 0 hr(r)hr(r
) = Dδ(r − r
)
Two	
  new	
  randomness	
  sources	
  means	
  two	
  new	
  physical	
  parameters	
  to	
  be	
  introduced…	
  	
  
λ(r) = 0 λ(r)λ(r
) = Aδ(r − r
)
R(r)R(r
) = 2KBTδ(r − r
)δ(t − t
)R(r) = 0
Random	
  field	
  
Temperature	
  noise	
  
Anisotropy	
  disorder	
  
Random	
  field	
  and	
  random	
  anisotropy	
  has	
  the	
  same	
  effect	
  on	
  the	
  domains	
  topography,	
  
except	
  that	
  the	
  type	
  of	
  domain	
  dynamics	
  (nucleaAon/coalescence	
  or	
  branching)	
  seems	
  to	
  
be	
  a	
  bit	
  more	
  sensiAve	
  to	
  A	
  than	
  D.	
  
Ironing	
  stripe	
  domains	
  
No	
  disorder	
  (realizaAon	
  1)	
   No	
  disorder	
  (realizaAon	
  2)	
   Gaussian	
  disorder	
  
•  The	
  final	
  orientaAon	
  of	
  the	
  parallel	
  stripes	
  depends	
  on	
  the	
  iniAal	
  random	
  configuraAon	
  
•  The	
  presence	
  of	
  disorder	
  inhibits	
  the	
  complete	
  reorientaAon	
  	
  
OscillaAng	
  external	
  field	
  perpendicular	
  to	
  the	
  film	
  surface:	
  
he(r) = h0 sin(ωt)
ω = 0.0126  Γµ0 ≡ 1 h0 = 2  hsat  4
Memory	
  effects	
  
Hysteresis	
  loop	
  unrolled:	
  
Ame	
  
m
Memory	
  effects	
  
Hysteresis	
  loop	
  unrolled:	
  
Ame	
  
Φ
˙m = α

dV
dm
+ ∇2
m

− γ

dr m(r
)
|r − r|3
+ hr(r) + h
In-­‐plane	
  Magne'za'on	
  	
  
Just	
  modifying	
  the	
  dipolar	
  (stray)	
  field,	
  our	
  scalar	
  model	
  seems	
  to	
  be	
  able	
  to	
  reproduce	
  the	
  
domain	
  dynamics	
  of	
  in-­‐plane	
  films.	
  	
  
	
  
Now	
  the	
  magneAzaAon	
  is	
  assumed	
  to	
  be	
  oriented	
  only	
  along	
  the	
  x-­‐axis	
  ranging	
  in	
  [-­‐1,+1]	
  an	
  
External	
  field	
  is	
  applied	
  along	
  the	
  same	
  axis	
  to	
  record	
  hysteresis	
  loops.	
  
+γ

dr 2(x − x
)2
− (y − y
)2
|r − r|
m(r
)
Open	
  Issues:	
  
Which	
  quanAAes	
  can	
  be	
  used	
  to	
  characterize	
  the	
  memory	
  effects	
  and	
  the	
  stripes	
  domains?	
  
	
  
	
  
One	
  Hysteresis	
  loop	
  takes	
  24	
  hours:	
  
•  Do	
  we	
  really	
  need	
  to	
  be	
  so	
  slow	
  in	
  increasing	
  the	
  field?	
  
•  How	
  many	
  loops	
  to	
  test	
  memory	
  effects?	
  
•  (Easy)	
  ParallelizaAon	
  will	
  speed	
  up	
  our	
  calculaAons	
  by	
  a	
  factor	
  of	
  4	
  
	
  
	
  
Up	
  to	
  now	
  we	
  used	
  only	
  white	
  noise,	
  does	
  it	
  make	
  sense	
  to	
  define	
  a	
  characterisAc	
  length	
  
for	
  the	
  noise	
  correlaAon?	
  
	
  
	
  
Working	
  in	
  reciprocal	
  space	
  enable	
  us	
  to	
  deal	
  with	
  large	
  systems	
  but	
  we	
  are	
  forced	
  to	
  use	
  
periodic	
  boundary	
  condiAons.	
  Edge	
  effects	
  cannot	
  be	
  taken	
  into	
  account	
  in	
  the	
  simulaAons	
  
	
  
	
  
In	
  the	
  case	
  of	
  a	
  bubbles	
  lamce,	
  can	
  we	
  play	
  with	
  an	
  external	
  oscillaAng	
  field	
  in	
  the	
  same	
  
way	
  we	
  do	
  for	
  stripe	
  domains,	
  to	
  try	
  to	
  order	
  the	
  lamce?	
  	
  	
  	
  	
  

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Nucleation and avalanches in film with labyrintine magnetic domains

  • 1. Nuclea'on  and  avalanches     in  films  with  labyrinthine   magne'c  domains   Andrea  Benassi  &   Stefano  Zapperi    
  • 2. Outline   Experiments  on  labyrinthine  domains     Our  phase  field  model     Characteris>cs  Lengths  and  avalanche  sta>s>cs         A  new  version  of  the  phase  field  model     Ironing  stripe  domains     Memory  effects               In-­‐plane  magne>za>on:  very  preliminary  results  (yesterday)  
  • 3. Labyrinthine  domains   Phys.Rev.Le*.  92,   077206  (2004)         Phys.Rev.B  71,   104431  (2005)   Deconvolving   nucleaAon   they  find  a  0.5   exponent  
  • 4. Labyrinthine  domains   Avalanche  staAsAcs  taken  over   different  intervals  of  the  hysteresis   loop  show  different  criAcal  exponents   Appl.Phys.Le*.  95,  182504  (2009)  
  • 5. A  phase  field  model   V = Ku 4 m2 2 − m4 4 m = M(r) Ms = m(x, y)
  • 6. A  phase  field  model   V = Ku 4 m2 2 − m4 4 m = M(r) Ms = m(x, y) ∂M(r, t) ∂t = −Γ δH[M(r, t)] δM(r, t) Energy  funcAonal  power  expansion   +   linear  relaAon  between  Ame  and   energy  fluctuaAons   Small  Ame   fluctuaAons   hypothesis  
  • 7. A  phase  field  model   hr(r) = 0 hr(r)hr(r ) = Dδ(r − r ) V = Ku 4 m2 2 − m4 4 m = M(r) Ms = m(x, y) ∂M(r, t) ∂t = −Γ δH[M(r, t)] δM(r, t) Energy  funcAonal  power  expansion   +   linear  relaAon  between  Ame  and   energy  fluctuaAons   Small  Ame   fluctuaAons   hypothesis   2  dimensionless   parameters   = 2 A/Ku α = Ku/4µ0M2 s γ = d/4π
  • 8. A  phase  field  model   hr(r) = 0 hr(r)hr(r ) = Dδ(r − r ) V = Ku 4 m2 2 − m4 4 m = M(r) Ms = m(x, y) ∂M(r, t) ∂t = −Γ δH[M(r, t)] δM(r, t) Energy  funcAonal  power  expansion   +   linear  relaAon  between  Ame  and   energy  fluctuaAons   Small  Ame   fluctuaAons   hypothesis   2  dimensionless   parameters   = 2 A/Ku α = Ku/4µ0M2 s γ = d/4π
  • 9. Two  different  limit  behaviors   Depending  on  the  film   thickness  and  on  the  disorder   strength  we  can  have  two  limit   behaviors   -4 -2 0 -0.5 0 0.5 42 b c d f a γ = 0.5 γ = 0.6 γ = 0.7 h e g b c da f g he
  • 10. Two  different  limit  behavors   MulAple  nucleaAon  and   coalescence  by  bridging   Expansion  by  branching  of  a  single   domain  and  lateral  fa*ening    
  • 11. Characteris'c  lengths   m(x, y, d) = sin πx d m(x, y, w) = tanh x w d = α/γ domain width w = √ 2 domain wall width n nucleation diameter MinimizaAon  of  the  energy  with  respect  to  a   fixed  magneAzaAon  configuraAon  with  one   parameter:   NucleaAon  depends  strongly  on  disorder,  any   analyAcal  theory  is  useless!!!  
  • 12. Characteris'c  lengths   m(x, y, d) = sin πx d m(x, y, w) = tanh x w d = α/γ domain width w = √ 2 domain wall width n nucleation diameter MinimizaAon  of  the  energy  with  respect  to  a   fixed  magneAzaAon  configuraAon  with  one   parameter:   NucleaAon  depends  strongly  on  disorder,  any   analyAcal  theory  is  useless!!!   Avalanches  
  • 13. Triggering  of  minor  avalanches   The  difference  between   consecuAve  magneAzaAon   maps  allows  a  direct  imaging   of  avalanches    
  • 14. Avalanche  sta's'cs   Analysis  of  different  loop  regions:     •  The  maximum  avalanche  size  decreases  as   the  domain  density  reaches  its  maximum   •  NucleaAon  and  bridging,  with  their   characterisAc  size,  affect  the  size   distribuAon           NucleaAon  and  annihilaAon:       •  For  nucleaAon  to  take  place  a  barrier  must   be  overcame,  its  value  goes  as  1/γ •  AnnihilaAon  is  almost  independent  of  the   dipolar  field  strength   •  At  zero  temperature  the  gaussian   distribuAon  is  due  to  the  spaAal  disorder  
  • 15. Avalanche  sta's'cs   Different  film  thickness:     •  The  avalanche  cutoff  increases  when  γ  is   decreased,  following  the  corresponding   increase  of  the  domain  width  and   confirming  that  α/γ  is  the  relevant   parameter  controlling  the  size  of  the   scaling  regime   Different  Disorder  strength:     •  The  Larger  D  the  larger  the  external  field  at   which  walls  depin,  the  larger  their  jumps.     •  Increasing  D  the  domains  shape  is  slightly   affected  by  the  disorder  strength  but              is   almost  independent  of  D,   •  NucleaAon  diameter              decreases  with   increasing  D   d = α n nucleation diame
  • 16. Phase  field  model  reloaded   V = [1 − λ(r)] ¯Ku 4 m2 2 − m4 4 ˙m = α dV dm + ∇2 m − γ dr m(r ) |r − r|3 + hr(r) + he(t) + R(t) hr(r) = 0 hr(r)hr(r ) = Dδ(r − r ) Two  new  randomness  sources  means  two  new  physical  parameters  to  be  introduced…     λ(r) = 0 λ(r)λ(r ) = Aδ(r − r ) R(r)R(r ) = 2KBTδ(r − r )δ(t − t )R(r) = 0 Random  field   Temperature  noise   Anisotropy  disorder   Random  field  and  random  anisotropy  has  the  same  effect  on  the  domains  topography,   except  that  the  type  of  domain  dynamics  (nucleaAon/coalescence  or  branching)  seems  to   be  a  bit  more  sensiAve  to  A  than  D.  
  • 17. Phase  field  model  reloaded   V = [1 − λ(r)] ¯Ku 4 m2 2 − m4 4 ˙m = α dV dm + ∇2 m − γ dr m(r ) |r − r|3 + hr(r) + he(t) + R(t) hr(r) = 0 hr(r)hr(r ) = Dδ(r − r ) Two  new  randomness  sources  means  two  new  physical  parameters  to  be  introduced…     λ(r) = 0 λ(r)λ(r ) = Aδ(r − r ) R(r)R(r ) = 2KBTδ(r − r )δ(t − t )R(r) = 0 Random  field   Temperature  noise   Anisotropy  disorder   Random  field  and  random  anisotropy  has  the  same  effect  on  the  domains  topography,   except  that  the  type  of  domain  dynamics  (nucleaAon/coalescence  or  branching)  seems  to   be  a  bit  more  sensiAve  to  A  than  D.  
  • 18. Ironing  stripe  domains   No  disorder  (realizaAon  1)   No  disorder  (realizaAon  2)   Gaussian  disorder   •  The  final  orientaAon  of  the  parallel  stripes  depends  on  the  iniAal  random  configuraAon   •  The  presence  of  disorder  inhibits  the  complete  reorientaAon     OscillaAng  external  field  perpendicular  to  the  film  surface:   he(r) = h0 sin(ωt) ω = 0.0126 Γµ0 ≡ 1 h0 = 2 hsat 4
  • 19. Memory  effects   Hysteresis  loop  unrolled:   Ame   m
  • 20. Memory  effects   Hysteresis  loop  unrolled:   Ame   Φ
  • 21. ˙m = α dV dm + ∇2 m − γ dr m(r ) |r − r|3 + hr(r) + h In-­‐plane  Magne'za'on     Just  modifying  the  dipolar  (stray)  field,  our  scalar  model  seems  to  be  able  to  reproduce  the   domain  dynamics  of  in-­‐plane  films.       Now  the  magneAzaAon  is  assumed  to  be  oriented  only  along  the  x-­‐axis  ranging  in  [-­‐1,+1]  an   External  field  is  applied  along  the  same  axis  to  record  hysteresis  loops.   +γ dr 2(x − x )2 − (y − y )2 |r − r| m(r )
  • 22. Open  Issues:   Which  quanAAes  can  be  used  to  characterize  the  memory  effects  and  the  stripes  domains?       One  Hysteresis  loop  takes  24  hours:   •  Do  we  really  need  to  be  so  slow  in  increasing  the  field?   •  How  many  loops  to  test  memory  effects?   •  (Easy)  ParallelizaAon  will  speed  up  our  calculaAons  by  a  factor  of  4       Up  to  now  we  used  only  white  noise,  does  it  make  sense  to  define  a  characterisAc  length   for  the  noise  correlaAon?       Working  in  reciprocal  space  enable  us  to  deal  with  large  systems  but  we  are  forced  to  use   periodic  boundary  condiAons.  Edge  effects  cannot  be  taken  into  account  in  the  simulaAons       In  the  case  of  a  bubbles  lamce,  can  we  play  with  an  external  oscillaAng  field  in  the  same   way  we  do  for  stripe  domains,  to  try  to  order  the  lamce?