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FeSi binary alloy electronic structure low-Si dataset (1024 atoms)

  • Lupo Pasini, Massimiliano | Oak Ridge National Laboratory
  • Reeve, Sam | Oak Ridge National Laboratory
  • Samolyuk, German | Oak Ridge National Laboratory
  • Ellis, Dean | Oak Ridge National Laboratory
  • Eisenbach, Markus | Oak Ridge National Laboratory
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Overview

Description

This dataset contaims the calculated atomic charge density, atomic magnetic moment, and total energy for 1600 configurations of iron-silicon (Fe-Si) binary alloys body-centered cubic (BCC) structures at 3, 6, and 9% Si. These large scale (1024 atom) ab initio calculations were produced with the LSMS code on the OLCF Summit supercomputer. LSMS GitHub repository: https://github.com/mstsuite/lsms

Funding resources

DOE contract number

DE-AC05-00OR22725

Originating research organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Other contributing organizations

Oak Ridge Leadership Computing Facility (OLCF)

Sponsoring organization

Office of Science (SC)

Details

DOI

10.13139/ORNLNCCS/1765080

Release date

February 15, 2021

Dataset

Dataset type

ND Numeric Data

Acknowledgements

Papers using this dataset are requested to include the following text in their acknowledgements:

*Support for 10.13139/ORNLNCCS/1765080 is provided by the U.S. Department of Energy, project MAT020 under Contract DE-AC05-00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.

Category

  • 36 MATERIALS SCIENCE,
  • 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,
  • 75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY

Keywords

  • machine learning,
  • alloy,
  • first principles