ase-bimetall

Atomic Simulation Environment scripts for BIMETALLic nanoparticles

Description

The collection of my scripts for Atomic Simulation Environment (ASE) used for study of bimetallic nanoparticles. The required ASE libraries are available at official site under free license.

Implemented (Reverse) Monte-Carlo method for the search of two-component structures based on the coordination numbers information. The MC class and Move nethods are heavily based on ASAP3 implementation.

Scripts

• analyzecn.py -- procedure-driven calculation of coordination numbers and similar quantities. Should be replaced by object oriented version QSAR;

• qsar.py -- class for calculation of coordination numbers and similar quantities;

• coreshell.py -- procedures to build atomic clusters with particular architecture;

• mc_search.py -- Monte-Carlo search of structures with known coordination numbers. Based on MC code from ASAP project.

Examples

• Import libraries

  from ase import Atom, Atoms
  from coreshell import sphericalFCC, randomize_biatom

• Build a spherical nanoparticle and stores it in Atoms object:

  atoms = sphericalFCC('Ag', 4.09, 8)

• Add some Pt atoms:

  atoms = randomize_biatom(atoms, 'Pt', 'Ag', ratio=0.6)

• You can view the structure using ASE in a very simple way:

  from ase.visualize import view
  view(atoms)

  

• Find out coordination numbers:

  from qsar import QSAR
  
  qsar = QSAR(atoms)
  
  qsar.biatomic('Pt', 'Ag')
  
  print( qsar.report_CNs() )

  The output will like:

  Coordination numbers:
      Pt-Pt   6.364
      Pt-Ag   4.058
      Ag-Pt   6.097
      Ag-Ag   4.340
  
  

• The Monte-Carlo example can be found in __main__ method in mc_search.py.