Elsevier Science Home
Computer Physics Communications Program Library
Full text online from Science Direct
Programs in Physics & Physical Chemistry
CPC Home

[Licence| Download | New Version Template] aewi_v1_0.tar.gz(40 Kbytes)
Manuscript Title: PyDII: A Python Framework for Computing Equilibrium Intrinsic Point Defect Concentrations and Extrinsic Solute Site Preferences in Intermetallic Compounds
Authors: Hong Ding, Bharat Medasani, Wei Chen, Kristin Persson, Maciej Haranczyk, Mark Asta
Program title: PyDII
Catalogue identifier: AEWI_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 193(2015)118
Programming language: Python.
Computer: Any computer with a Python interpreter.
Operating system: Any which enable Python.
RAM: Problem dependent
Keywords: Intrinsic Point Defect, Extrinsic Solute Site Preference, Intermetallic Compound, Phython.
Classification: 7.1.

External routines: NumPy [1], Sympy [2], and Pymatgen [3],

Nature of problem:
Equilibrium intrinsic point defect concentrations and solute site preferences in intermetallic compounds.

Solution method:
Intrinsic point defect properties and solute site preference as a function of composition and temperature are computed within the grand-canonical, dilute-solution thermodynamic formalism developed by Woodward et al., Phys. Rev. B 63 (2001) 094103.

Restrictions:
The current version of PyDII supports generating inputs and parsing outputs for density functional calculations implemented in VASP. Defect energetics obtained from other computational methods or software can also be used to compute the defect properties by preparing the input in conformation with the format of JSON files provided in example folder.

Additional comments:
This article describes version 1.0.0.

Running time:
Problem dependent

References:
[1] Numpy Developers, http://numpy.org/.
[2] Sympy Development Team, http://sympy.org/.
[3] S. P. Ong, W. D. Richards, A. Jain, G. Hautier, M. Kocher, S. Cholia, D. Gunter, V. L. Chevrier, K. A. Persson, G. Ceder, Python Materials Genomics (pymatgen) : A Robust, Open-Source Python Library for Materials Analysis, Computational Materials Science 68 (2013) 314-319.