Published February 11, 2023 | Version 1.0
Dataset Open

Iron nanoparticle database

Creators

  • 1. Aalto University

Description

This is a database of Fe nanoparticles generated with a GAP interatomic potential for iron [1]. The files are provided in ASE's extended XYZ format. For each nanoparticle, convex_hull.xyz includes the energies as computed with:

  • PAW-PBE DFT [1,2]
  • our GAP [3]
  • the GAP by Dragoni et al. [4]
  • the EAM by Mendelevet al. [5]
  • the EAM by Finnis and Sinclair et al. [6]

The movie surface.mp4 shows the fractions of surface sites resembling surface motifs from pristine crystal surfaces more than the others, for each particle from convex_hull.xyz. Similarity is measured by comparing SOAP descriptors [7] of the surface environments with those from the reference structures.

More details can be found in this arXiv preprint:

Searching for iron nanoparticles with a general-purpose Gaussian approximation potential

Richard Jana, Miguel A. Caro

https://doi.org/10.1103/PhysRevB.107.245421

The authors are grateful to the Academy of Finland for financial support under projects #321713 (R. J. & M.A. C.) and #330488 (M.A. C.), and CSC -- IT Center for Science as well as Aalto University's Science-IT Project for computational resources.

Files

surface.mp4

Files (3.9 MB)

Name Size Download all
md5:706eed1cebbfb7dd3bc386dde2a7dd44
2.6 MB Download
md5:b40bb6cdc223614b6de6668f5c3338b1
1.3 MB Preview Download

Additional details

Funding

Next-generation interatomic potentials to simulate new cellulose-based materials (NEXTCELL) 330488
Academy of Finland
Towards accurate computational experimentation (COMPEX): machine-learning-driven simulation of nanocarbon synthesis 321713
Academy of Finland

References

  • [1] Kresse, G., Joubert, D. (1999). Physical Review B - Condensed Matter and Materials Physics, 59(3), 1758–1775.
  • [2] J.P. Perdew, K. Burke, and M. Ernzerhof. Phys Rev. Lett. 77, 3865 (1996).
  • [3] Jana, Richard, & Caro, Miguel A. (2023). GAP general purpose interatomic potential for iron (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7630369
  • [4] Dragoni, D., Daff, T. D., Csányi, G., Marzari, N. (2018). Physical Review Materials, 2, 13808.
  • [5] Mendelev, M. I., Han, S., Srolovitz, D. J., Ackland, G. J., Sun, D. Y., Asta, M. (2003). Philosophical Magazine, 83(35), 3977–3994.
  • [6] Finnis, M. W., Sinclair, J. E. (1984). Philisophical Magazine, 50(1), 45–55.
  • [7] A.P. Bartók, R. Kondor, and G. Csányi. Phys. Rev. B 87, 184115 (2013).