Modeling of the magnetic properties of nanomaterials with different crystalline structure

TL;DR

This paper introduces a modeling approach for nanomaterials' magnetic properties using the Ising model and random field approximation, enabling analysis across various structures and shapes with good experimental agreement.

Contribution

It presents a unified, algorithmic method to calculate magnetization in nanomaterials of different structures by adjusting exchange integrals within the Ising model framework.

Findings

Accurately models magnetization for diverse nanostructures.

Predicts Curie temperature based on nanostructure parameters.

Aligns well with experimental data.

Abstract

We propose a method for modeling the magnetic properties of nanomaterials with different structures. The method is based on the Ising model and the approximation of the random field interaction. It is shown that in this approximation, the magnetization of the nanocrystal depends only on the number of nearest neighbors of the lattice atoms and the values of exchange integrals between them. This gives a good algorithmic problem of calculating the magnetization of any nano-object, whether it is ultrathin film or nanoparticle of any shape and structure, managing only a rule of selection of nearest neighbors. By setting different values of exchange integrals, it is easy to describe ferromagnets, antiferromagnets, and ferrimagnets in a unified formalism. Having obtained the magnetization curve of the sample it is possible to find the Curie temperature as a function of, for example, the thickness of ultrathin film. Afterwards one can obtain the numerical values for critical exponents of the phase transition "ferromagnet -- paramagnet". Good agreement between the results of calculations and the experimental data proves the correctness of the method.