TaZr_BCC_SolidSolution_128atoms_VASP6
- Samolyuk, German | Oak Ridge National Laboratory
- Eisenbach, Markus | Oak Ridge National Laboratory
- Lupo Pasini, Massimiliano | Oak Ridge National Laboratory
- Choi, Jong Youl | Oak Ridge National Laboratory
- Rogers, David | Oak Ridge National Laboratory
- Yang, Ying | Oak Ridge National Laboratory
Overview
Description
We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys tantalum-zirconium (Ta-Zr).
The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Ta and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials.
The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites.
We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions.
The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2.
The VASP calculations for every atomic structure have been performed in 2 main steps:
1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out.
2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'.
Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128.
Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included.
The files contained in each sub-directory 'case-*' for each atomic structure are as follows:
FILES contained in each subdirectory with name "case-N" where N ranges between 11 and 80, extremes included:
1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations
2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone
3. 0.POSCAR: input file that defines the atomic structure of a system
4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file
5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file
6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file
7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file
8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file
9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file
10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file
11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support
12. vasprun.xml: contains similar information to OUTCAR, but in an xml format.
13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system
FILES contained in each subdirectory with name "case-N" where N ranges between 1 and 10 and between 81 and 100, extremes included:
1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations
2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone
3. {ID}.POSCAR: input file that defines the atomic structure of a system at the beginning of ID execution of geometry optimization with PREC=LOW
4. {ID}.CONTCAR: output file that provides the atomic positions and cell parameters at the end of ID execution of geometry optimization with PREC=LOW in the INCAR file
5. {ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of geometry optimization that has been run with the precision variable set to PREC=Low in the INCAR file
6. rlx1.{ID}.out: file with diagnostic information about the execution of the ID execution of the geometry optimization with precision variable set to PREC=Low in the INCAR file
7. N{ID}.POSCAR: input file that defines the atomic structure of a system after the geometry optimization run at low precision. This represents the input for the ID execution of the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file
8. N{ID}.CONTCAR: output file that provides the atomic positions and cell parameters after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file
9. N{ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file
10. rlx2.{ID}.out: file with diagnostic information about the ID execution of geometry optimization with precision variable set to PREC=Normal in the INCAR file
11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support
12. vasprun.xml: contains similar information to OUTCAR, but in an xml format.
13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system
This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725.
This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216.
REFERENCES
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(3) Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15–50 (1996)
(4) Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996)
(5) Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)
Funding resources
DOE contract number
DE-AC05-00OR22725Originating research organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Other contributing organizations
National Energy Research Scientific Computing Center (NERSC), Berkeley, CA (United States)Sponsoring organization
Office of Science (SC); ORNL Laboratory Directed Research and Development (LDRD)Details
DOI
10.13139/OLCF/2466324Release date
October 30, 2024Dataset
Dataset type
ND Numeric DataSoftware
Python; PyTorch; PyTorch-Geometric, Atomic Simulation Environment (ASE)Acknowledgements
Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:
This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.
Category
- 74 ATOMIC AND MOLECULAR PHYSICS,
- 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,
- 75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY,
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY,
- 36 MATERIALS SCIENCE
Keywords
- First Principles,
- Machine Learning,
- Solid Solution Alloys,
- Density Functional Theory