
BVlain is a python library for bond valence site energy calculations. The functionality includes calculation of the 1-3D percolation barrier and radius of a mobile ion (e.g. Li+), calculation of the bond valence sum mismatch, writing of volumetric data files (.grd or .cube) for visualization of a mobile ion diffusion map.
For more details, see documentation.
Installation
pip install bvlain
Examples
Percolation barriers
from bvlain import Lain
file = '/Users/artemdembitskiy/Downloads/LiFePO4.cif'
calc = Lain(verbose = False)
st = calc.read_file(file)
params = {'mobile_ion': 'Li1+',
'r_cut': 10.0,
'resolution': 0.2,
'k': 100
}
_ = calc.bvse_distribution(**params)
energies = calc.percolation_barriers(encut = 5.0)
for key in energies.keys():
print(f'{key[-2:]} percolation barrier is {round(energies[key], 4)} eV')
1D percolation barrier is 0.4395 eV
2D percolation barrier is 3.3301 eV
3D percolation barrier is 3.3594 eV
Percolation radii
from bvlain import Lain
file = '/Users/artemdembitskiy/Downloads/LiFePO4.cif'
calc = Lain(verbose = False)
st = calc.read_file(file)
params = {'mobile_ion': 'Li1+',
'r_cut': 10.0,
'resolution': 0.2,
}
_ = calc.void_distribution(**params)
radii = calc.percolation_radii()
for key in radii.keys():
print(f'{key[-2:]} percolation barrier is {round(radii[key], 4)} angstrom')
1D percolation barrier is 0.3943 angstrom
2D percolation barrier is 0.2957 angstrom
3D percolation barrier is 0.1972 angstrom
Save volumetric data for visualization (.grd or .cube)
from bvlain import Lain
file = '/Users/artemdembitskiy/Downloads/LiFePO4.cif'
calc = Lain(verbose = False)
st = calc.read_file(file)
params = {'mobile_ion': 'Li1+',
'r_cut': 10.0,
'resolution': 0.2,
'k': 100
}
_ = calc.bvse_distribution(**params)
_ = calc.void_distribution(**params)
calc.write_grd(file + '_bvse', task = 'bvse')
calc.write_cube(file + '_void', task = 'void')
Bond valence sum mismatch
from bvlain import Lain
file = '/Users/artemdembitskiy/Downloads/LiFePO4.cif'
calc = Lain(verbose = False)
st = calc.read_file(file)
dataframe = calc.mismatch(r_cut = 3.5)
For more examples, see documentation.
The library is under active development and it is not guaranteed that there are no bugs. If you observe not expected results, errors, please report an issue at github.