相关论文: Determination of the Dzyaloshinskii-Moriya interac…
The capabilities of image probe experiments are rapidly expanding, providing new information about quantum materials on unprecedented length and time scales. Many such materials feature inhomogeneous electronic properties with intricate…
The Dzyaloshinskii-Moriya interaction (DMI), which is essential for the stabilization of topologically non-trivial chiral magnetic textures such as skyrmions, is particularly strong in heterostructures of ultra-thin magnetic materials and…
Machine Learning (ML) has the potential to accelerate discovery of new materials and shed light on useful properties of existing materials. A key difficulty when applying ML in Materials Science is that experimental datasets of material…
We study Dzyaloshinskii-Moriya interaction (DMI) appearing at the interface of a nonmagnetic/noncollinear-antiferromagnetic bilayer. DMI is an antisymmetric exchange interaction between neighboring magnetic spins, arising in the absence of…
This paper reviews machine learning applications and approaches to detection, classification and control of intelligent materials and structures with embedded distributed computation elements. The purpose of this survey is to identify…
We demonstrate here that ultrathin ferromagnetic Pt/Co/Pt films with perpendicular magnetic anisotropy exhibit a sizeable Dzyaloshinskii-Moriya interaction (DMI) effect. Such a DMI effect modifies the domain-wall (DW) energy density and…
Determination of the energy of Dzyaloshinskii-Moriya interaction along with a definition of the basic magnetic characteristics in ferromagnetic/nonmagnetic multilayered systems are both required for the construction of a magnetic skyrmion…
Recent results show remarkable interfacial--Dzyaloshinskii--Moriya interaction (i-DMI) in magnetic heterostructures composed of relatively thick Fe thin films ($\gg 1$ nm). To investigate its origin, we present a thorough magnetic…
We study in this paper effects of Dzyaloshinskii-Moriya (DM) magnetoelectric coupling between ferroelectric and magnetic layers in a superlattice formed by alternate magnetic and ferroelectric films.Magnetic films are films of simple cubic…
In the ongoing research on two-dimensional (2D) ferromagnetic materials with strong intrinsic Dzyaloshinskii--Moriya interaction (DMI), most efforts have focused on doping, Janus engineering, or heterostructure formation to break inversion…
The Dzyaloshinskii-Moriya interaction (DMI) is an antisymmetric exchange interaction, which is responsible for the formation of topologically protected spin textures in chiral magnets. Here, by measuring the dispersion relation of the DM…
We estimate the spatial distribution of heterogeneous physical parameters involved in the formation of magnetic domain patterns of polycrystalline thin films by using convolutional neural networks. We propose a method to obtain a spatial…
We utilize statistical tools to analyze the magnetic domain wall dynamics in a nanostrip, which can quantify the magnitude and reveal the effects of interfacial Dzyaloshinskii-Mariya interaction. We find that there exist two peaks in the…
In this report we review the method of explicit calculations of interatomic exchange interactions of magnetic materials. This involves exchange mechanisms normally referred to as Heisenberg exchange, Dzyaloshinskii-Moriya interaction and…
Two of the most widely used electronic structure theory methods, namely Hartree-Fock and Kohn-Sham density functional theory, both requires the iterative solution of a set of Schr\"odinger-like equations. The speed of convergence of such…
Interfacial Dzyaloshinskii-Moriya interaction (DMI) is experimentally investigated in Pt/Co/Pt multilayer films under strain. A strong variation (from 0.1 to 0.8 mJ/m$^2$) of the DMI constant is demonstrated at $\pm 0.1\%$ in-plane uniaxial…
The interfacial Dzyaloshinskii-Moriya interaction (DMI) in the ferromagnetic/heavy metal ultra-thin film structures , has attracted a lot of attention thanks to its capability to stabilize Neel-type domain walls (DWs) and magnetic skyrmions…
Deep neural networks are used to model the magnetization dynamics in magnetic thin film elements. The magnetic states of a thin film element can be represented in a low dimensional space. With convolutional autoencoders a compression ratio…
Deep learning models are widely used for the data-driven design of materials based on atomic force microscopy (AFM) and other scanning probe microscopy. These tools enhance efficiency in inverse design and characterization of materials.…
The magnetic exchange interaction is the one of the key factors governing the basic characteristics of magnetic systems. Unlike the symmetric nature of the Heisenberg exchange interaction, the interfacial Dzyaloshinskii-Moriya interaction…