Running Common Neighbor Analysis

The Common Neighbor Analysis (CNA) uses the local crystal structure to find defects. In this script a cluster is melted and then cooled down again so it solidifies. Restricted CNA (looking only for FCC, HCP and "other" structures) is used to look for atoms sitting in local crystalline order, and plots are made of a cut through the cluster using PrimiPlotter.

In the beginning, the cluster is molten, and nothing in particular is seen. Towards the end of the simulation, it solidifies and the center of the cluster is seen to contain atoms in FCC order (white), and a relatively large number of atoms in HCP order (red). These are stacking faults, created because the cooling was so fast. The actual phase transition is not seen, it happens at a temperature where the thermal vibrations makes it impossible for CNA to determine the structure. See the example Running Polyhedral Template Matching for an alternative method.

This script uses a chain of observers. The RestrictedCNA object is attached as an observer to the Langevin dynamics, and is called at regular intervals. The PrimiPlotter is then attached to the RestrictedCNA object, and is called immediately after CNA analysis has been performed.


A cut through the cluster. FCC atoms are white, HCP atoms red and all other atoms are blue.

"Melting a copper cluster."

from numpy import *
from asap3 import Atoms, EMT, units
from asap3.analysis.localstructure import RestrictedCNA
from ase.visualize.primiplotter import *
from ase.lattice.cubic import FaceCenteredCubic
from import Langevin

# Create the atoms
atoms = FaceCenteredCubic(size=(6,6,6), symbol="Cu", pbc=False)

# Associate the EMT potential with the atoms

# Temperature profile - brief run at 1750, then lower temperature gradually
t = linspace(1500, 250, 81)
temperatures = 1500 * ones(100)
temperatures[-len(t):] = t
print temperatures

# How many steps at each temperature
nsteps_total = 100000
nsteps = nsteps_total // len(temperatures)

# Interval between plots
plotinterval = 2000

# Make the Langevin dynamics module
dyn = Langevin(atoms, 5*units.fs, units.kB*temperatures[0], 0.002)

# The CNA analyser is called every plotinterval timesteps.
cna = RestrictedCNA(atoms)
dyn.attach(cna.analyze, interval=plotinterval)

# The plotter
def invisible_atoms(a):
    """Return True for atoms that should be invisible."""
    r = atoms.get_positions()
    centerofmass = r.sum(axis=0) / len(atoms)
    return (r[:,2] < centerofmass[2])

plotter = PrimiPlotter(atoms)
plotter.set_colors({0: (1.0, 1.0, 1.0), 1: (1.0, 0.0, 0.0), 2: (0.3, 0.3, 1.0)}) # Map tags to colors
# plotter.set_output(X11Window())   # Plot in a window on the screen
plotter.set_output(GifFile("plt"))  # Save plots in files plt0000.gif ...
plotter.set_rotation((10.0, 5.0, 0))

# Attach the plotter to the RestrictedCNA object.  That guarantees
# that the plotter is called AFTER the CNA analysis has been done.
# Similarly, a Trajectory should be attached to the RestricedCNA
# object.  By using interval=1 (the default), the plotter is called
# every time RestrictedCNA is called, i.e. every plotinterval
# timesteps.

# The main loop
for t in temperatures:
    for i in range(nsteps/100):
        print "E_total = %-10.5f  T = %.0f K  (goal: %.0f K, step %d of %d)" %\
              (atoms.get_total_energy()/len(atoms), atoms.get_temperature(), t, i, nsteps/100)

Asap: Running Common Neighbor Analysis (last edited 2016-04-06 12:03:47 by JakobSchiøtz)