CuAu binary alloy with 32 atoms - LSMS-3 data

Dataset · Mon Feb 15 04:00:00 EST 2021

DOI:https://doi.org/10.13139/OLCF/1765349· OSTI ID:1765349

Pasini, Massimiliano Lupo ^[1]; Eisenbach, Markus

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1. ORNL-OLCF

This dataset contains the estimate of atomic charge density, atomic magnetic moment and total energy for 32,000 configurations of the iron-platinum (CuAu) binary alloy with face-centered cubic (FCC) structure. The configurations span all the compositions from 0%Cu - 100% Au through 100%Cu - 0% Au. The results have been produced running ab-initio density functional theory (DFT) calculations with the LSMS-3 code on OLCF supercomputer Titan. LSMS-3 GitHub repository: https://github.com/mstsuite/lsms Deep Learning research papers published with results based on this dataset: "Fast and stable deep-learning predictions of material properties for solid solution alloys" Massimiliano Lupo Pasini, Ying Wai Li, Junqi Yin, Jiaxin Zhang, Kipton Barros and Markus Eisenbach Published 14 December 2020 • © 2020 IOP Publishing Ltd Journal of Physics: Condensed Matter, Volume 33, Number 8 Citation Massimiliano Lupo Pasini et al 2021 J. Phys.: Condens. Matter 33 084005 https://iopscience.iop.org/article/10.1088/1361-648X/abcb10

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: Office of Science (SC)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1765349
• Country of Publication: United States
• Language: English

Related Subjects

36 MATERIALS SCIENCE
71 CLASSICAL AND QUANTUM MECHANICS
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75 CONDENSED MATTER PHYSICS
SUPERCONDUCTIVITY AND SUPERFLUIDITY
machine learning
alloy
first principles