相关论文: Determination of the Dzyaloshinskii-Moriya interac…
Different models of dark matter can alter the distribution of mass in galaxy clusters in a variety of ways. However, so can uncertain astrophysical feedback mechanisms. Here we present a Machine Learning method that ''learns'' how the…
This study examines the application of machine learning algorithms, specifically the Random Forest regression model, to optimize the magnetocaloric effect in all-d-metal Heusler alloys. The model was trained using descriptors related to the…
\hspace{2mm} Diffusion-weighted magnetic resonance imaging (dMRI) of the brain offers unique capabilities including noninvasive probing of tissue microstructure and structural connectivity. It is widely used for clinical assessment of…
The inclusion of a Dzyaloshinskii-Moriya short range antisymmetric interaction induces spontaneous magnetization, at nonzero temperatures, in one and two dimensions. It is shown that quantum fluctuations are reduced by the…
A micromorphic computational homogenization framework has recently been developed to deal with materials showing long-range correlated interactions, i.e. displaying patterning modes. Typical examples of such materials are elastomeric…
We study in this paper magnetic properties of a system of quantum Heisenberg spins interacting with each other via a ferromagnetic exchange interaction J and an in-plane Dzyaloshinskii-Moriya interaction D. The non-collinear ground state…
The magnetic interfacial Dzyaloshinskii-Moriya interaction (DMI) in multi-layered thin films can lead to exotic chiral spin states, of paramount importance for future spintronic technologies. Interfacial DMI is normally manifested as an…
Interfacial Dzyaloshinskii-Moriya interaction (iDMI) has been investigated in Co2FeAl (CFA) ultrathin films of various thicknesses (0.8 nm<tCFA<2 nm) grown on Si substrates, using Pt, W, Ir and MgO buffer or/and capping layers. Vibrating…
The Dzyaloshinskii-Moriya interaction (DMI) has drawn great attention as it stabilizes magnetic chirality, with important implications in fundamental and applied research. This antisymmetric exchange interaction is induced by the broken…
The Dzyaloshinskii Moriya Interaction (DMI) at the heavy metal (HM) and ferromagnetic metal (FM) interface has been recognized as a key ingredient in spintronic applications. Here we investigate the chemical trend of DMI on the 5d band…
We present results of the analysis of Brillouin Light Scattering (BLS) measurements of spin waves performed on ultrathin single and multirepeat CoFeB layers with adjacent heavy metal layers. From a detailed study of the spin-wave dispersion…
The Dzyaloshinskii-Moriya interaction (DMI) has attracted considerable recent attention owing to the intriguing physics behind and the fundamental role it played in stabilizing magnetic solitons, such as magnetic skyrmions and chiral domain…
Quantitative descriptions of the structure-thermal property correlation have been a bottleneck in designing materials with superb thermal properties. In the past decade, the first-principles phonon calculations using density functional…
Machine Learning (ML) plays an increasingly important role in the discovery and design of new materials. In this paper, we demonstrate the potential of ML for materials research using hard-magnetic phases as an illustrative case. We build…
Currently, the growth of material data from experiments and simulations is expanding beyond processable amounts. This makes the development of new data-driven methods for the discovery of patterns among multiple lengthscales and time-scales…
Interfacial Dzyaloshinskii-Moriya interaction (iDMI) in interlayer exchange coupled (IEC) Pt/Co$_{20}$Fe$_{60}$B$_{20}$(1.12 nm)/Ru/Co$_{20}$Fe$_{60}$B$_{20}$(1.12 nm) systems have been studied theoretically and experimentally. Vibrating…
Machine-learned coarse-grained (MLCG) molecular dynamics is a promising option for modeling biomolecules. However, MLCG models currently require large amounts of data from reference atomistic molecular dynamics or substantial computation…
Machine learning promises to deliver powerful new approaches to neutron scattering from magnetic materials. Large scale simulations provide the means to realise this with approaches including spin-wave, Landau Lifshitz, and Monte Carlo…
For magnetic materials containing many lattice imperfections (e.g., nanocrystalline magnets), the relativistic Dzyaloshinski-Moriya (DM) interaction may result in nonuniform spin textures due to the lack of inversion symmetry at interfaces.…
Many important multi-component crystalline solids undergo mechanochemical spinodal decomposition: a phase transformation in which the compositional redistribution is coupled with structural changes of the crystal, resulting in dynamically…