PyDII: A python framework for computing equilibrium intrinsic point defect concentrations and extrinsic solute site preferences in intermetallic compounds

Point defects play an important role in determining the structural stability and mechanical behavior of intermetallic compounds. To help quantitatively understand the point defect properties in these compounds, we developed PyDII, a Python program that performs thermodynamic calculations of equilibrium intrinsic point defect concentrations and extrinsic solute site preferences in intermetallics. The algorithm implemented in PyDll is built upon a dilute-solution thermodynamic formalism with a set of defect excitation energies calculated from first-principles density-functional theory methods. The analysis module in PyDII enables automated calculations of equilibrium intrinsic antisite and vacancy concentrations as a function of composition and temperature (over ranges where the dilute solution formalism is accurate) and the point defect concentration changes arising from addition of an extrinsic substitutional solute species. To demonstrate the applications of PyDll, we provide examples for intrinsic point defect concentrations in NiAl and Al3 V and site preferences for Ti, Mo and Fe solutes in NiAl. Program summary Program title: PyDII Catalogue identifier: AEWI_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEWI_vl_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: MIT License No. of lines in distributed program, including test data, etc.: 6123 No. of bytes in distributed program, including test data, etc.: 40988 Distribution format: tar.gz Programming language: Python. Computer: Any computer with a Python interpreter. Operating system: Any which enable Python. RAM: Problem dependent 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 a format consistent with that of the JSON files provided in the 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. (C) 2015 Elsevier B.V. All rights reserved.