Classification of atoms as solid or liquid#

pyscal can also be used to distinguish solid and liquid atoms. The classification is based on Steinhardt’s parameters, specifically \(q_6\). The method defines two neighboring atoms \(i\) and \(j\) as having solid bonds if a parameter \(s_{ij}\) [1],

\[ s_{ij} = \sum_{m=-6}^6 q_{6m}(i) q_{6m}^*(j) \geq \mathrm{threshold} \]

Additionally, a second order parameter is used to improve the distinction in solid-liquid boundaries [2]. This is defined by the criteria,

\[ \langle s_{ij} \rangle > \mathrm{avgthreshold} \]

If a particle has \(n\) number of bonds with \(s_{ij} \geq \mathrm{threshold}\) and the above condition is also satisfied, it is considered as a solid. The solid atoms can be clustered to find the largest solid cluster of atoms.

Finding solid atoms in liquid start with reading in a file and calculation of neighbors.

from pyscal3 import System
sys = System('conf.dump')
sys.find.neighbors(method='cutoff', cutoff=4)

Once again, there are various methods for finding neighbors. Once the neighbors are calculated, solid atoms can be found directly by,

sys.find.solids(bonds=6, threshold=0.5, avgthreshold=0.6, cluster=True)

bonds set the number of minimum bonds a particle should have (as defined above), threshold and avgthreshold are the same quantities that appear in the equations above. Setting the keyword cluster to True returns the size of the largest solid cluster. It is also possible to check if each atom is solid or not.

sys.atoms.solid

References#

Auer, S. & Frenkel, D. Numerical Simulation of Crystal Nucleation in Colloids. in Advanced Computer Simulation: Approaches for Soft Matter Sciences I (eds. Dr. Holm, C. & Prof. Dr. Kremer, K.) 149–208 (Springer Berlin Heidelberg, Berlin, Heidelberg, 2005). doi:10.1007/b99429.
Bokeloh, J., Wilde, G., Rozas, R. E., Benjamin, R. & Horbach, J. Nucleation barriers for the liquid-to-crystal transition in simple metals: Experiment vs. simulation. European Physical Journal: Special Topics 223, 511–526 (2014).