4.7 Article

The Effect of Vacancies on Grain Boundary Segregation in Ferromagnetic fcc Ni

期刊

NANOMATERIALS
卷 10, 期 4, 页码 -

出版社

MDPI
DOI: 10.3390/nano10040691

关键词

fcc Ni; tilt Sigma 5(210) grain boundary; vacancy; Si and Al impurity; grain boundary energy; segregation energy; defects binding energies; magnetism

资金

  1. Grant Agency of the Czech Republic [GA16-24711S]
  2. Ministry of Education, Youth and Sports of the Czech Republic (CEITEC 2020) [LQ1601]
  3. Academy of Sciences of the Czech Republic [RVO:68081723]

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This work presents a comprehensive and detailed ab initio study of interactions between the tilt Sigma 5(210) grain boundary (GB), impurities X (X = Al, Si) and vacancies (Va) in ferromagnetic fcc nickel. To obtain reliable results, two methods of structure relaxation were employed: the automatic full relaxation and the finding of the minimum energy with respect to the lattice dimensions perpendicular to the GB plane and positions of atoms. Both methods provide comparable results. The analyses of the following phenomena are provided: the influence of the lattice defects on structural properties of material such as lattice parameters, the volume per atom, interlayer distances and atomic positions; the energies of formation of particular structures with respect to the standard element reference states; the stabilization/destabilization effects of impurities (in substitutional (s) as well as in tetragonal (iT) and octahedral (iO) interstitial positions) and of vacancies in both the bulk material and material with GBs; a possibility of recombination of Si-(i)+Va defect to Si-(s) one with respect to the Va position; the total energy of formation of GB and Va; the binding energies between the lattice defects and their combinations; impurity segregation energies and the effect of Va on them; magnetic characteristics in the presence of impurities, vacancies and GBs. As there is very little experimental information on the interaction between impurities, vacancies and GBs in fcc nickel, most of the present results are theoretical predictions, which may motivate future experimental work.

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