# Getting started 04: Current induced domain wall motion¶

Interactive online tutorial: In this tutorial we show how Zhang-Li spin transfer torque (STT) can be included in micromagnetic simulations. To illustrate that, we will try to move a domain wall pair using spin-polarised current.

Let us simulate a two-dimensional sample with length $L = 500 \,\text{nm}$, width $w = 20 \,\text{nm}$ and discretisation cell $(2.5 \,\text{nm}, 2.5 \,\text{nm}, 2.5 \,\text{nm})$. The material parameters are:

• exchange energy constant $A = 15 \,\text{pJ}\,\text{m}^{-1}$,
• Dzyaloshinskii-Moriya energy constant $D = 3 \,\text{mJ}\,\text{m}^{-2}$,
• uniaxial anisotropy constant $K = 0.5 \,\text{MJ}\,\text{m}^{-3}$ with easy axis $\mathbf{u}$ in the out of plane direction $(0, 0, 1)$,
• gyrotropic ratio $\gamma = 2.211 \times 10^{5} \,\text{m}\,\text{A}^{-1}\,\text{s}^{-1}$, and
• Gilbert damping $\alpha=0.3$.
In :
import oommfc as oc
import discretisedfield as df
import micromagneticmodel as mm
%matplotlib inline

# Definition of parameters
L = 500e-9  # sample length (m)
w = 20e-9  # sample width (m)
d = 2.5e-9  # discretisation cell size (m)
Ms = 5.8e5  # saturation magnetisation (A/m)
A = 15e-12  # exchange energy constant (J/)
D = 3e-3  # Dzyaloshinkii-Moriya energy constant (J/m**2)
K = 0.5e6  # uniaxial anisotropy constant (J/m**3)
u = (0, 0, 1)  # easy axis
gamma0 = 2.211e5  # gyromagnetic ratio (m/As)
alpha = 0.3  # Gilbert damping

# Mesh definition
p1 = (0, 0, 0)
p2 = (L, w, d)
cell = (d, d, d)
region = df.Region(p1=p1, p2=p2)
mesh = df.Mesh(region=region, cell=cell)

# Micromagnetic system definition
system = mm.System(name='domain_wall_pair')
system.energy = mm.Exchange(A=A) + \
mm.DMI(D=D, crystalclass="Cnv") + \
mm.UniaxialAnisotropy(K=K, u=u)
system.dynamics = mm.Precession(gamma0=gamma0) + mm.Damping(alpha=alpha)


Because we want to move a DW pair, we need to initialise the magnetisation in an appropriate way before we relax the system.

In :
def m_value(pos):
x, y, z = pos
if 20e-9 < x < 40e-9:
return (0, 0, -1)
else:
return (0, 0, 1)

system.m = df.Field(mesh, dim=3, value=m_value, norm=Ms)

system.m.z.plane('z').k3d_scalar()


Now, we can relax the magnetisation.

In :
md = oc.MinDriver()
md.drive(system)

system.m.z.plane('z').k3d_scalar()

Running OOMMF (ExeOOMMFRunner) [2020/06/12 00:40]... (8.4 s)


Now we can add the STT term to the dynamics equation.

In :
ux = 400  # velocity in x-direction (m/s)
beta = 0.5  # non-adiabatic STT parameter

system.dynamics += mm.ZhangLi(u=ux, beta=beta)  # please notice the use of += operator


And drive the system for $0.5 \,\text{ns}$:

In :
td = oc.TimeDriver()
td.drive(system, t=0.5e-9, n=100)

system.m.z.plane('z').k3d_scalar()

Running OOMMF (ExeOOMMFRunner) [2020/06/12 00:40]... (6.0 s)


We see that the DW pair has moved to the positive $x$ direction.

## Exercise 1¶

Modify the code below (which is a copy of the example from above) to obtain one domain wall instead of a domain wall pair and move it using the same current.

In :
# Definition of parameters
L = 500e-9  # sample length (m)
w = 20e-9  # sample width (m)
d = 2.5e-9  # discretisation cell size (m)
Ms = 5.8e5  # saturation magnetisation (A/m)
A = 15e-12  # exchange energy constant (J/)
D = 3e-3  # Dzyaloshinkii-Moriya energy constant (J/m**2)
K = 0.5e6  # uniaxial anisotropy constant (J/m**3)
u = (0, 0, 1)  # easy axis
gamma0 = 2.211e5  # gyromagnetic ratio (m/As)
alpha = 0.3  # Gilbert damping

# Mesh definition
p1 = (0, 0, 0)
p2 = (L, w, d)
cell = (d, d, d)
region = df.Region(p1=p1, p2=p2)
mesh = df.Mesh(region=region, cell=cell)

# Micromagnetic system definition
system = mm.System(name='domain_wall')
system.energy = mm.Exchange(A=A) + \
mm.DMI(D=D, crystalclass='Cnv') + \
mm.UniaxialAnisotropy(K=K, u=u)
system.dynamics = mm.Precession(gamma0=gamma0) + mm.Damping(alpha=alpha)

def m_value(pos):
x, y, z = pos
# Modify the following line
if 20e-9 < x < 40e-9:
return (0, 0, -1)
else:
return (0, 0, 1)
# We have added the y-component of 1e-8 to the magnetisation to be able to
# plot the vector field. This will not be necessary in the long run.

system.m = df.Field(mesh, dim=3, value=m_value, norm=Ms)

system.m.z.plane('z').k3d_scalar()

In :
md = oc.MinDriver()
md.drive(system)

system.m.z.plane('z').k3d_scalar()

Running OOMMF (ExeOOMMFRunner) [2020/06/12 00:40]... (8.2 s)

In :
ux = 400  # velocity in x direction (m/s)
beta = 0.5  # non-adiabatic STT parameter

system.dynamics += mm.ZhangLi(u=ux, beta=beta)

td = oc.TimeDriver()
td.drive(system, t=0.5e-9, n=100)

system.m.z.plane('z').k3d_scalar()

Running OOMMF (ExeOOMMFRunner) [2020/06/12 00:40]... (5.6 s)