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MuMax3 is best suited for mesoscale simulations, meaning it can model magnetization behavior at the micro- and nano-scale, which is crucial for understanding domain structures, coercivity, and thermal stability.
What it is: The field strength required to reverse magnetization in a material.
Why it matters: High coercivity prevents unwanted demagnetization.
How to compute in MuMax3:
Set up a magnetic system (e.g., NdFeB grains).
Apply an external field sweep (e.g., a decreasing field in the opposite direction).
Track magnetization reversal () as a function of the field.
Find the field strength at which magnetization crosses zero.
Example Code (lua):
B_ext = vector(1, 0, 0) * 2e-1 -- Apply an external field (T)
relax() -- Let the system reach equilibrium
tablesave() -- Save initial state
-- Sweep field to determine coercivity
for B = 0, -1, -0.01 do
B_ext = vector(1, 0, 0) * B
minimize() -- Find new equilibrium
tablesave() -- Save data
end
Result: Plot to extract .
What it is: The full magnetization curve showing how a magnet responds to an external field.
Why it matters: The area enclosed in the hysteresis loop determines the maximum energy stored in a magnet.
How to compute in MuMax3:
Run a full field loop (+H to -H and back).
Extract remanence () and coercivity ().
Calculate energy product from and .
Example Code:
for B = -1, 1, 0.01 do
B_ext = vector(B, 0, 0)
relax()
tablesave()
end
for B = 1, -1, -0.01 do
B_ext = vector(B, 0, 0)
relax()
tablesave()
end
Result: Use plot to find .
What it is: The formation of magnetic domains and their evolution under applied fields.
Why it matters: Domain structure impacts coercivity and magnetization reversal.
How to compute in MuMax3:
Define grain sizes and magnetic parameters.
Simulate relaxation to find equilibrium states.
Apply a small perturbation and track domain wall motion.
Example Code:
Aex = 1e-11 -- Exchange stiffness
Ku1 = 1e6 -- Anisotropy constant
Msat = 1.2e6 -- Saturation magnetization
alpha = 0.02 -- Damping parameter
-- Initial magnetization state
m = randomMag()
relax() -- Find domain equilibrium
-- Apply small external field pulse
B_ext = vector(0.01, 0, 0)
run(1e-9)
Result: Observe domain wall motion in MuMax3’s visualization.
What it is: The ability of a magnet to retain its properties at high temperatures.
Why it matters: High prevents thermal demagnetization.
How to compute in MuMax3:
Introduce a random thermal noise field.
Measure how magnetization decreases over time.
Extract an effective Curie temperature based on changes in .
Example Code:
Temp = 300 -- Set temperature (K)
alpha = 0.02 -- Damping
thermalnoise = true -- Enable thermal fluctuations
run(1e-9) -- Simulate magnetization decay
tablesave() -- Save final magnetization state
Result: Fit the curve to estimate .
What it is: The energy required to rotate magnetization out of its easy axis.
Why it matters: Strong anisotropy prevents unwanted switching.
How to compute in MuMax3:
Set uniaxial anisotropy with varying field angles.
Measure energy barriers for magnetization switching.
Example Code:
Ku1 = 5e5 -- High anisotropy constant
m = uniform(1, 0, 0) -- Start along easy axis
-- Apply external field along different angles
B_ext = vector(0.1, 0, 0)
relax()
tablesave()
Result: Extract energy barrier values to confirm high coercivity.
MuMax3 works at the micromagnetic scale (~nm to µm). However, some properties require atomic-scale calculations, such as:
Electronic structure (e.g., Density Functional Theory for Curie temperature)
Intrinsic anisotropy (DFT calculations needed for Ku1 values)
Magneto-elastic effects (Requires coupled micromagnetic and structural modeling)
Solution: Combine MuMax3 (micromagnetic) with DFT calculations (quantum-scale) from tools like VASP, Quantum ESPRESSO, or Material Project data.
Property | Can MuMax3 Compute It? | Notes |
---|---|---|
Coercivity () | ✅ Yes | Field sweep method |
Hysteresis Loop () | ✅ Yes | Full magnetization cycle |
Magnetization Dynamics | ✅ Yes | Time-dependent micromagnetics |
Domain Structures | ✅ Yes | Relaxation + visualization |
Thermal Stability | ✅ Yes | Random thermal noise modeling |
Curie Temperature () | ⚠️ Indirectly | Requires extrapolating |
Anisotropy Energy | ✅ Yes | Switching field method |
Electronic Structure | ❌ No | Use DFT (VASP, QE, etc.) |
MuMax3 is great for micromagnetic modeling, but not for atomic-scale properties. We should use:
MuMax3 → Micromagnetic simulations for coercivity, domain walls, hysteresis.
DFT (Quantum ESPRESSO, VASP, Materials Project) → Intrinsic material properties like , , and .
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