SingleCrystal.jl

Building single crystal structures easily
Author eschmidt42
Popularity
1 Star
Updated Last
1 Year Ago
Started In
January 2021

SingleCrystal.jl

With this package you can create single crystal structures. The implementation is based on the Python ase package.

Installation

To install, open your Julia REPL and enter

import Pkg
Pkg.add("https://github.com/eschmidt42/SingleCrystal.jl#master")

or alternatively via the package manager (enter in the REPL via ]) and type add https://github.com/eschmidt42/SingleCrystal.jl#master.

Usage

Let's say you want to create a body centered cubic (bcc) unit cell (💡 wiki 💡). The general approach to create it or any other crystal's unit cell would be as follows:

symbols = ["Fe"] # chemical elements
basis = [[0. 0. 0.],] # scaled coordinates
nr = 229 # space group
setting = 1 # space group settig (greetings from ase)
cellpar = [2.87, 2.87, 2.87, 90, 90, 90]; # specification of the 3 cell vector lengths (in Å = 10⁻¹⁰m) a, b, c and three angles (in degrees) α, β, γ

crystal = SingleCrystal.make_unitcell(basis, symbols, nr, setting, cellpar)

For the case of bcc unit cells, you could alternatively also use the less verbose path via the make_bcc_unitcell convenience function:

crystal = SingleCrystal.make_bcc_unitcell("Fe", 3.4)

In case you want to replicate the unit cell along the cell vectors to create a supercell, you can use make_supercell:

supercell = SingleCrystal.make_supercell(crystal, nx=3, ny=3, nz=3);

For more examples, and a peek behind the curtains of the ase algorithm implemented in this package, I encourage you to check out docs/singl_crystals_in_julia.ipynb. There you can also find the above examples in context and find how to create a vacancy *spoiler*.

Happy crystal synthesizing! 😃

Motivation

The main objective for this package is to prepare input required for the Molecular Dynamics package Molly.jl, to simulate body centered cubic single crystals.

A minimal working example for the usage of SingleCrystal.jl with Molly.jl (based on a fork of Molly.jl adding the Finnis-Sinclair potential type - a pull request of the fork is currently under review):

import Pkg
Pkg.activate(".") # if you are in the root of the forked Molly.jl package

using Molly
using SingleCrystal

fs_inter, elements, masses, bcc_lattice_constants, reference_energies = Molly.get_finnissinclair1984(true)
make_atom(name,mass) = Atom(name=name,mass=mass)

# setting up the crystal
nx = 3
ny = 3
nz = 3
element = "Fe"

a = bcc_lattice_constants[element]
crystal = SingleCrystal.make_bcc_unitcell(element, a, make_atom)
supercell = SingleCrystal.make_supercell(crystal, nx=nx, ny=ny, nz=nz)

# setting up the simulation
T = 100. # Kelvin
T = T*fs_inter.kb
n_steps = 2500
dt = .002 # ps; ns = 1e-9s, ps = 1e-12s, fs = 1e-15s
n_atoms = length(supercell.atoms)
general_inters = (fs_inter,)
velocities = [velocity(supercell.atoms[i].mass, T, dims=3) for i in 1:n_atoms]
nb_matrix = trues(n_atoms,n_atoms)
dist_cutoff = 2 * a
nf = DistanceNeighbourFinder(nb_matrix, 1, dist_cutoff)
thermostat = NoThermostat()

loggers = Dict(
    "temperature" => TemperatureLogger(1),
    "pot" => EnergyLogger(1),
)

s = Simulation(
    simulator=VelocityVerlet(), 
    atoms=supercell.atoms, 
    general_inters=general_inters,
    coords=[SVector{3}(v) for v in supercell.positions], 
    velocities=velocities,
    temperature=T, 
    box_size=supercell.edge_lengths[1],
    timestep=dt,
    n_steps=n_steps,
    neighbour_finder=nf,
    loggers=loggers,
)

# running the simulation
simulate!(s) 

To dos

  1. Add more crystal structures to test beyond those in the ase gallery
  2. Test how the performance / resource requirements scale with crystal size / number of atoms

Contributing

Contributions are very welcome.

Required Packages

Used By Packages

No packages found.