Dataset D146

Contact details

Alexandra GORYAEVA, Saclay Nuclear Research Centre (CEA Saclay)

Email: alexandra.goryaeva@cea.fr

Additional attribution details

alternative contact:  mihai-cosmin.marinica@cea.fr

Acknowledgements

This work has been carried out within the framework of the  EUROfusion  Consortium and has received funding from the  Euratom research and training programme 2014-2018 and 2019-2020 under grant agreement No 633053.  The views and opinions expressed herein do not necessarily reflect those of the  European  Commission.  
Computational resources are provided GENCI  -  (CINES/CCRT) computer centre under Grant No.  A0090906973.

Citation

B53: A. M. Goryaeva , J. Dérès, C. Lapointe, P. Grigorev, T. D. Swinburne, J.R. Kermode, L. Ventelon, J. Baima , M.-C. Marinica, "Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W", Physical Review Materials 00, 003800 (2021). [link to article]

System composition: Fe_126

Number of atoms: 126

Number of atom types: 1

Matrix: Fe

Structure: bcc

Reference (bulk) structure calculation:

Point Defects

vacancy: 2 Fe

Content comments:

Molecular dynamics of di-vacancy at 800 K, a0=2.83413

Calculation type: molecular dynamics

Code: VASP 5.4.1

Exchange correlation: GGA

Exchange correlation comment: GGA

kpoints: 4 4 4 0.5 0.5 0.5

E_cut: 500.0 eV

Smearing type: Methfessel-Paxton

Smearing energy: 0.1 eV

Electronic density convergence criterion: 0.00000001

Magnetism included? Yes

Pseudopotential

Name: "Fe"

Class: paw

Semicore? No

Archive URL: https://db-amdis.org/defectdb/data/agoryaeva/Fe_PRM/Fe_V2_MD_800K.tar.gz

Vacancy