sknano.generators.SWNTBundleGenerator

class sknano.generators.SWNTBundleGenerator(autogen=True, **kwargs)

Class for generating nanotube bundles.

New in version 0.2.4.

Parameters:

n, m : int

Chiral indices defining the nanotube chiral vector \(\mathbf{C}_{h} = n\mathbf{a}_{1} + m\mathbf{a}_{2} = (n, m)\).

nx, ny, nz : int, optional

Number of repeat unit cells in the \(x, y, z\) dimensions.

element1, element2 : {str, int}, optional

Element symbol or atomic number of basis Atom 1 and 2

bond : float, optional

\(\mathrm{a}_{\mathrm{CC}} =\) distance between nearest neighbor atoms. Must be in units of Angstroms.

vdw_spacing : float, optional

van der Waals distance between nearest neighbor tubes

New in version 0.2.5.

bundle_packing : {‘hcp’, ‘ccp’}, optional

Packing arrangement of nanotubes bundles. If bundle_packing is None, then it will be determined by the bundle_geometry parameter if bundle_geometry is not None. If both bundle_packing and bundle_geometry are None, then bundle_packing defaults to hcp.

New in version 0.2.5.

bundle_geometry : {‘triangle’, ‘hexagon’, ‘square’, ‘rectangle’}, optional

Force a specific geometry on the nanotube bundle boundaries.

New in version 0.2.5.

Lx, Ly, Lz : float, optional

length of bundle in \(x, y, z\) dimensions in nanometers. Overrides the \(n_x, n_y, n_z\) cell values.

New in version 0.2.5.

fix_Lz : bool, optional

Generate the nanotube with length as close to the specified \(L_z\) as possible. If True, then non integer \(n_z\) cells are permitted.

New in version 0.2.6.

autogen : bool, optional

if True, automatically call generate_unit_cell, followed by generate_structure_data.

verbose : bool, optional

if True, show verbose output

Examples

Using the SWNTBundleGenerator class, you can generate structure data for nanotube bundles with either cubic close packed (ccp) or hexagonal close packed (hcp) arrangement of nanotubes. The bundle packing arrangement is set using the bundle_packing parameter.

You can also enforce a specific bundle geometry which will try and build the nanotube bundle such that it “fits inside” the boundaries of a specified geometric shape. This allows you to generate hcp bundles that are trianglar, hexagonal, or rectangular in shape, as some of the examples below illustrate.

To start, let’s generate an hcp bundle of \(C_{\mathrm{h}} = (10, 5)\) SWCNTs and cell count \(n_x=10, n_y=3, n_z=5\).

>>> from sknano.generators import SWNTBundleGenerator
>>> SWCNTbundle = SWNTBundleGenerator(n=10, m=5, nx=10, ny=3, nz=5)
>>> SWCNTbundle.save_data()

The rendered structure looks like:

Now let’s generate a nice hexagon bundle, 3 tubes wide, with \(C_{\mathrm{h}} = (6, 5)\).

>>> SWCNTbundle = SWNTBundleGenerator(n=6, m=5, nz=5,
...                                   bundle_geometry='hexagon')
>>> SWCNTbundle.save_data()

which looks like:

Remember, all of the save_data methods allow you to rotate the structure data before saving:

>>> SWCNTbundle.save_data(fname='0605_hcp_7tube_hexagon_rot-30deg.xyz',
...                       rot_axis='z', rotation_angle=30)

Now, just because we can, let’s make a big ass hexagon bundle with \(C_{\mathrm{h}} = (10, 0)\).

>>> BIGASSHEXABUN = SWNTBundleGenerator(10, 0, nx=25, ny=25, nz=1,
...                                     bundle_geometry='hexagon')
>>> BIGASSHEXABUN.save_data()

Take a look at the 469 \((10, 0)\) unit cells in this big ass bundle!

Lastly, here’s a look at a bundle generated with cubic close packed bundle arrangement:

>>> SWCNTbundle = SWNTBundleGenerator(10, 10, nx=3, ny=3, nz=5,
...                                   bundle_packing='ccp')
>>> SWCNTbundle.save_data()

The rendered ccp structure looks like:

Attributes

Ch	SWNT circumference \(|\mathbf{C}_h|\) in Å
Lx
Ly
Lz	SWNT length \(L_z = L_{\mathrm{tube}}\) in nanometers.
M	\(M = np - nq\)
N	Number of graphene hexagons in nanotube unit cell.
Natoms	Number of atoms in nanotube.
Natoms_per_bundle
Natoms_per_tube	Number of atoms in nanotube \(N_{\mathrm{atoms/tube}}\).
Natoms_per_unit_cell	Number of atoms in nanotube unit cell.
Ntubes
R	Symmetry vector \(\mathbf{R} = (p, q)\).
T	Length of nanotube unit cell \(|\mathbf{T}|\) in Å.
atoms	Return structure Atoms.
bond	Bond length in Å.
bundle_density
bundle_mass
bundle_packing
chiral_angle	Chiral angle \(\theta_c\) in degrees.
chiral_type
d	\(d=\gcd{(n, m)}\)
dR	\(d_R=\gcd{(2n + m, 2m + n)}\)
dt	Nanotube diameter \(d_t = \frac{|\mathbf{C}_h|}{\pi}\) in Å.
electronic_type	SWNT electronic type.
element1	Element symbol of Atom 1.
element2	Element symbol of Atom 2.
fix_Lz
linear_mass_density	Linear mass density of nanotube in g/nm.
m	Chiral index \(m\).
n	Chiral index \(n\).
nx	Number of nanotubes along the \(x\)-axis.
ny	Number of nanotubes along the \(y\)-axis.
nz	Number of nanotube unit cells along the \(z\)-axis.
rt	Nanotube radius \(r_t = \frac{|\mathbf{C}_h|}{2\pi}\) in Å.
structure	Alias to structure_data.
structure_data	Return StructureData instance.
t1	\(t_{1} = \frac{2m + n}{d_{R}}\)
t2	\(t_2 = -\frac{2n + m}{d_R}\)
tube_length	Alias for SWNT.Lz
tube_mass	SWNT mass in grams.
unit_cell_mass	Unit cell mass in atomic mass units.
unit_cell_symmetry_params

Methods

compute_bundle_params()	Compute/update nanotube bundle parameters.
generate_bundle()
generate_structure_data()	Generate structure data.
generate_unit_cell()	Generate the nanotube unit cell.
save_data([fname, outpath, ...])	Save structure data.
todict()	Return dict of SWNT attributes.