Decahedral particle¶
- class wulffpack.Decahedron(surface_energies, twin_energy, primitive_structure=None, natoms=1000, tol=1e-05)[source]¶
A Decahedron object is a generalized Wulff construction of a decahedral particle.
- Parameters
surface_energies (
Dict
[tuple
,float
]) – A dictionary with surface energies, where keys are Miller indices and values surface energies (per area) in a unit of choice, such as J/m^2.twin_energy (
float
) – Energy per area for twin boundariesprimitive_structure (
Optional
[Atoms
]) – Primitive cell to define the atomic structure used if an atomic structure is requested. By default, an Au FCC structure is used. The crystal has to have cubic symmetry.natoms (
int
) – Together with lattice_parameter, this parameter defines the volume of the particle. If an atomic structure is requested, the number of atoms will as closely as possible match this value.tol (
float
) – Numerical tolerance parameter.
Example
The following example illustrates some possible uses of a Decahedron object:
>>> from wulffpack import Decahedron >>> from ase.build import bulk >>> from ase.io import write >>> surface_energies = {(1, 1, 1): 1.0, (1, 0, 0): 1.14} >>> prim = bulk('Au') >>> particle = Decahedron(surface_energies, ... twin_energy=0.03, ... primitive_structure=bulk('Au')) >>> particle.view() >>> write('decahedron.xyz', particle.atoms) # Writes atomic structure
- property area: float¶
Returns total area of the surface of the particle (not including twin boundaries).
- Return type
- property aspect_ratio: float¶
Returns the aspect ratio of the decahedron, here defined as the ratio between the longest distance between two vertices projected on the fivefold axis versus the longest distance between two vertices projected on the plane perpendicular to the fivefold axis.
- Return type
- property atoms: ase.atoms.Atoms¶
Returns an ASE Atoms object
- Return type
Atoms
- property average_surface_energy: float¶
Average surface energy for the Wulff construction, i.e., a weighted average over all the facets, where the weights are the area fraction of each facet.
- Return type
- property facet_fractions: Dict[tuple, float]¶
Returns a dict specifying fraction of each form (not including twin boundaries).
- property fivefold_axis_vector: numpy.ndarray¶
Returns a vector pointing in the direction of the five-fold axis.
- Return type
ndarray
- property forms: List[wulffpack.core.form.Form]¶
List of inequivalent forms for the particle
- get_continuous_color_scheme(base_colors=None, normalize=False)¶
Returns a dictionary with RGB colors for each form. The colors smoothly interpolate between three base colors, corresponding to (1, 1, 1), (1, 1, 0) and (1, 0, 0). Note that this is sensible primarily for cubic systems.
- Parameters
- Return type
- get_strain_energy(shear_modulus, poissons_ratio)[source]¶
Return strain energy as estimated with the formula provided in A. Howie and L. D. Marks in Phil. Mag. A 49, 95 (1984) [HowMar84] (Eq. 10), which assumes an inhomogeneous strain in the particle.
Warning
This value is only approximate. If the decahedron is heavily truncated, the returned strain energy may be highly inaccurate.
- make_plot(ax, alpha=0.85, linewidth=0.3, colors=None)¶
Plot a particle in an axis object. This function can be used to make customized plots of particles.
- Parameters
Example
In the following example, three different particles are plotted in the same figure:
>>> from wulffpack import SingleCrystal, Decahedron, Icosahedron >>> import matplotlib.pyplot as plt >>> from mpl_toolkits.mplot3d import Axes3D >>> >>> surface_energies = {(1, 1, 1): 1.0, ... (1, 0, 0): 1.1, ... (1, 1, 0): 1.15, ... (3, 2, 1): 1.15} >>> twin_energy = 0.05 >>> >>> fig = plt.figure(figsize=(3*4.0, 4.0)) >>> ax = fig.add_subplot(131, projection='3d') >>> particle = SingleCrystal(surface_energies) >>> particle.make_plot(ax) >>> >>> ax = fig.add_subplot(132, projection='3d') >>> particle = Decahedron(surface_energies, ... twin_energy=0.05) >>> particle.make_plot(ax) >>> >>> ax = fig.add_subplot(133, projection='3d') >>> particle = Icosahedron(surface_energies, ... twin_energy=0.05) >>> particle.make_plot(ax) >>> >>> plt.subplots_adjust(top=1, bottom=0, left=0, ... right=1, wspace=0, hspace=0) >>> plt.savefig('particles.png')
- property natoms: List[int]¶
The approximate number of atoms in the particle (implicitly defining the volume).
- property number_of_corners: float¶
Returns the number of corners (vertices) on the particle.
- Return type
- rotate_particle(rotation)¶
Rotate the particle.
- Parameters
rotation (
ndarray
) – Rotation matrix
- property standardized_structure: ase.atoms.Atoms¶
The standardized atomic structure that defines the geometry and thus the meaning of the Miller indices. Also forms the building blocks when particle.atoms is called.
- Return type
Atoms
- property surface_energy: float¶
The total surface energy of the particle (including twin boundaries).
- Return type
- translate_particle(translation)¶
Translate the particle.
- Parameters
translation (list of 3 floats) – Translation vector
- view(alpha=0.85, linewidth=0.3, colors=None, legend=True, save_as=None)¶
Use matplotlib to view a rendition of the particle.
- Parameters
alpha (
float
) – Opacity of the faceslinewidth (
float
) – Thickness of lines between facescolors (
Optional
[dict
]) – Allows custom colors for facets of all or a subset of forms, example {(1, 1, 1): ‘#FF0000’}legend (
bool
) – Whether or not to show a legend with facet-color definitionssave_as (
Optional
[str
]) – Filename to save figure as. If None, show the particle with the GUI instead.