materialscloud:2023.180
Published November 22, 2023 | Version v1
Dataset Open

Relaxed thin film structures of one, two, and three magnetic 3d transition metal layers on FCC noble-metal substrates based on FLAPW PBE calculations

Creators

  • 1. Department of Physics, RWTH Aachen University, Aachen, Germany
  • 2. Institute for Advanced Simulation (IAS-1), Forschungszentrum Jülich and JARA, Jülich, Germany

* Contact person

Description

The uploaded data set contains setups of all 6660 possible combinations of up to three atomic layers of 3d transition metals on six different FCC noble-metal substrates. The substrates are modelled by five layers of Ag, Au, Pd, Pt, Rh or Ir in the (001) orientation. Nearly all structures (6282) have been relaxed, i.e. their ground state atomic configuration has been determined by density functional theory calculations. This has been achieved using a workflow implemented in the AiiDA-FLEUR package that first determines the substrate lattice constant and then relaxes the interlayer distances of the ad-layers using the forces calculated. All simulations have been performed using the FLAPW code FLEUR with the standard GGA-PBE exchange-correlation functional. A significant portion of these 3d thin films exhibits magnetic properties and thus could have applications in emerging technological fields such as e.g. spintronics. Therefore, the database also includes the magnetic properties of the relaxed films. However, no systematic investigation of possible magnetic configuration was performed and hence not in all cases the magnetic ground state might be included.

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References

Journal reference (PhD thesis discussing the simulation setup and utilization of the data)
R. Hilgers, PhD Thesis, RWTH Aachen (2024), doi: 10.18154/rwth-2024-09243

Preprint (Paper in which the simulation setup, context and data utilization is described)
R. Hilgers, D. Wortmann, and S. Blügel, arXiv (2023), doi: 10.48550/arXiv.2311.15430

Software (The FLEUR FLAPW code used for computation)
D. Wortmann et al., Zenodo (2023), doi: 10.5281/zenodo.7891361

Journal reference (AiiDA framework reference 1)
S. P. Huber et al., Scientific Data 7 (2020), doi: 10.1038/s41597-020-00638-4

Journal reference (AiiDA framework reference 2)
M. Uhrin et al., Computational Materials Science 187 (2021), doi: 10.1016/j.commatsci.2020.110086

Software (Used AiiDA-FLEUR plugin)
J. Bröder et al., Zenodo (2023), doi: 10.5281/zenodo.7893716

Software (Materials science tools used in the AiiDA-FLEUR plugin)
H. Janssen et al., Zenodo (2023), doi: 10.5281/zenodo.7892182