CrystalFieldSusceptibility¶

Description¶

This function calculates the crystal field contribution to the molar magnetic susceptibility using the Van Vleck formula. The function outputs the results by default in cgs units of cm³/mol == “emu/mol”. There are also options to output the result in SI (m³/mol) or “atomic” units (/Tesla/ion).

Theory¶

The magnetic susceptibility can be calculated by treating the magnetic field (Zeeman interaction) as a perturbation on the crystal field energy. To second order, the susceptibility per mole of magnetic ion is given by:

where is Avogadro’s constant, is Boltzmann’s constant, is the partition sum, and and are the n-th wavefunction (eigenvector) and energy level (eigenvalue) of the unperturbed crystal field Hamiltonian. is the Landé g-factor, is the Bohr magneton and the moment operator is defined as where , , and are the angular momentum operators in Cartesian coordinates, with defined to be along the quantisation axis of the crystal field (which is usually defined to be the highest symmetry rotation axis). , , and are the components of the unit vector pointing in the direction of the applied magnetic field in this coordinate system.

Finally, in order to account for the effect of any exchange interactions in the system which will shift the susceptibility curve up or down (analogous to the Curie-Weiss temperature), the actual magnetic susceptibility calculated by this function is:

where parameterises an effective exchange interaction and is the bare (paramagnetic Crystal Field) susceptibility. A negative indicates overall antiferromagnetic interactions, whilst a positive corresponds to overall ferromagnetic interactions.

Example¶

Here is an example of how to the crystal field parameters to a susceptibility dataset. All parameters disallowed by symmetry are fixed automatically. The “data” here is generated from the function itself, for a field along the [111] direction with respects to the crystal field parameters (not necessarily the [111] crystallographic direction).

The x-axis is given in Kelvin, and the susceptibility (y-axis) is in cgs units of cm³/mol (==emu/mol).

import numpy as np

# Build a reference data set
fun = 'name=CrystalFieldSusceptibility,Ion=Ce,B20=0.37737,B22=0.039770,B40=-0.031787,B42=-0.11611,B44=-0.12544,'
fun += 'Hdir=(1,1,1), Unit=cgs, inverse=1,'

# This creates a (empty) workspace to use with EvaluateFunction
x = np.linspace(1, 300, 300)
y = x * 0
e = y + 1
ws = CreateWorkspace(x, y, e)

# The calculated data will be in 'data', WorkspaceIndex=1
EvaluateFunction(fun, ws, OutputWorkspace='data')

 # Change parameters slightly and fit to the reference data
fun = 'name=CrystalFieldSusceptibility,Ion=Ce,Symmetry=C2v,B20=0.4,B22=0.04,B40=-0.03,B42=-0.1,B44=-0.1,'
fun += 'Hdir=(1,1,1), Unit=cgs, inverse=1,'
fun += 'ties=(B60=0,B62=0,B64=0,B66=0,BmolX=0,BmolY=0,BmolZ=0,BextX=0,BextY=0,BextZ=0)'

# (set MaxIterations=0 to see the starting point)
Fit(fun, 'data', WorkspaceIndex=1, Output='fit',MaxIterations=100, CostFunction='Unweighted least squares')
# Using Unweighted least squares fit because the data has no errors.

# Extract fitted parameters
parws = mtd['fit_Parameters']
for i in range(parws.rowCount()):
    row = parws.row(i)
    if row['Value'] != 0:
        print "%7s = % 7.5g" % (row['Name'], row['Value'])

Output (the numbers you see on your machine may vary):

    B20 =  0.37737
    B22 =  0.039788
    B40 = -0.031787
    B42 = -0.11611
    B44 = -0.12544
Cost function value =  1.0921e-14

Attributes (non-fitting parameters)¶

Properties (fitting parameters)¶

Categories: FitFunctions | General

Source¶

C++ source: CrystalFieldSusceptibility.cpp

C++ header: CrystalFieldSusceptibility.h