LAVA 1.0: A general-purpose python toolkit for calculation of material properties with LAMMPS and VASP

We introduce LAVA, a general-purpose python toolkit to provide user-friendly and high throughput calculations for material properties using both LAMMPS and VASP. It contains a set of classes as well as pre-processing and post-processing functions to prepare, execute and extract information from LAMM...

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Vydáno v:Computer physics communications Ročník 286; s. 108667
Hlavní autoři: Dang, Khanh, Chen, Jie, Rodgers, Brian, Fensin, Saryu
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Elsevier B.V 01.05.2023
Elsevier
Témata:
ISSN:0010-4655, 1879-2944
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Shrnutí:We introduce LAVA, a general-purpose python toolkit to provide user-friendly and high throughput calculations for material properties using both LAMMPS and VASP. It contains a set of classes as well as pre-processing and post-processing functions to prepare, execute and extract information from LAMMPS/VASP simulations. An overview of the program structure is provided. The current version contains modules to calculate elastic and mechanical properties such as lattice constant, cohesive energy, cold curve, elastic constants, bulk and shear modulus, volume conserving/non-conserving deformation path, vacancy/interstitial formation energy, surface energy, stacking fault energy, melting point, radial distribution function, and thermal expansion. These functionalities are demonstrated for different interatomic potentials and DFT calculations in Al. Program title: LAVA CPC Library link to program files:https://doi.org/10.17632/6grh8x4hgt.1 Licensing provisions: BSD 3-Clause License Programming language: Python Nature of problem: This program provides user-friendly and high throughput calculations for material properties via two widely-used LAMMPS and VASP code. Solution method: LAVA can prepare the input scripts, extract, calculate and even plot the material properties from molecular dynamics simulations and density functional calculations together with bash and python scripts.
Bibliografie:89233218CNA000001
LA-UR-22-22700
USDOE National Nuclear Security Administration (NNSA)
ISSN:0010-4655
1879-2944
DOI:10.1016/j.cpc.2023.108667