Magnetic characteristics of iron nanoclusters

The study of the nanocrystalline state, which significantly changes most of the physical characteristics of sub-stances, is very relevant. Of great practical interest are the works devoted to the study of the magnetic character-istics of nanocrystals of ferromagnetic substances. It has already been shown that the size of iron nanocrystals significantly affects the magnitude of their magnetization. Nevertheless, an adequate model of the structure of nanocrystalline formations consisting of a different number of iron atoms, which allows us to describe the exper-imentally detected changes in the magnetic characteristics, has not yet been presented. In this paper, we analyze nanocrystalline iron clusters that are different in configuration and number of their constituent atoms. Spatial models of clusters are constructed using a three-dimensional modeling program, and the coordinates of individual atoms in the cluster are determined. The proposed structures of nanocrystals are based on tetrahedrally close-packed cluster assemblies of iron atoms. The electron state density spectra were con-structed for the proposed clusters. For this purpose, the theory of the electron density functional was used, the calculation was carried out by the method of scattered waves in accordance with the band theory of crystals. It is shown that the appearance of magnetization in tetrahedral densely packed cluster formations is associat-ed with the excited electronic states of the atoms located on the surface of the nanocluster. Excited atoms have an increased electron density, that is, electrons are able to transition to states with higher energy, approaching the Fermi energy. In this case, the Stoner criterion necessary for the occurrence of magnetization is fulfilled. The con-figurations of electrons with spin up and down differ, which is why uncompensated magnetic moments appear. It is confirmed that the proposed models of iron nanoclusters satisfactorily correspond to the known experimental data.