چكيده لاتين
In recent years, there has been a significant increase in attention to devices made from multiferroic materials. This research focuses on materials such as BiFeO3 (bismuth ferrite), a multiferroic material; WTe2 (tungsten ditelluride), a Weyl semimetal; and AlN (aluminum nitride), which has a wurtzite structure. Given the recent rise in interest toward ferroelectric metals, WTe2 has been utilized as a ferroelectric metal in this study. Since electric polarization is a key feature in physics and engineering, our focus has been on calculating electric polarization for various materials. For the BiFeO3 structure, a G-type antiferromagnetic spin arrangement was considered, which is important for the arrangement of Fe (iron) atoms in this structure. Using the GGA+U approximation and a Hubbard potential of around 4 electron volts, the spontaneous electric polarization was calculated. For the WTe2 structure, a ferroelectric spin arrangement was used, where all spins were aligned. Due to the presence of d orbitals in the valence shell of W (tungsten) atoms, these atoms play a crucial role in the WTe2 structure. In this case, the GGA+U approximation was also used, with Hubbard potentials of 6, 6.5, and 7 electron volts. Furthermore, for the AlN structure, which is a semiconductor with a high energy bandgap, electric polarization was calculated. After determining the spontaneous polarization, each structure was subjected to hydrostatic pressure, and it was observed that the electric polarization increased with pressure. This increase in pressure and the electronic property calculations at high pressures can lead to the discovery of new materials with significant potential. In the next phase, impurities were introduced into the BiFeO3 and WTe2 structures. Recently, there has been considerable focus on the incorporation of indium (In) into various materials, particularly transition metal oxides, due to its desirable combination of suitable size and favorable electronic structure. In this study, indium atoms were considered as impurities, replacing Bi atoms in BiFeO3, and the spontaneous polarization of the InxBi1-xFeO3 compound was calculated. This modification resulted in an increase in ferroelectricity and electric polarization in the structure. Additionally, iron (Fe) atoms were introduced into the WTe2 structure, replacing tungsten atoms. This modification also led to an increase in ferromagnetic ordering and enhanced spontaneous electric polarization in the FexW1-xTe2 structure. To perform these calculations, supercells were used to maintain an equal number of atoms. Given the computationally heavy nature of density functional theory (DFT) methods, an artificial neural network algorithm with deep learning techniques was designed to reduce the computational load. This algorithm was applied to the AlN compound, and the results demonstrated that the predicted values of electric polarization, derived from the neural network, could significantly reduce computational time, making it highly useful for various applications.
