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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

Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:

This work was carried out [in part] at Oak Ridge National Laboratory, managed by UT-Battelle, LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725.

Category

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

Keywords

  • machine learning,
  • alloy,
  • first principles