Related papers: Classification of magnetic order from electronic s…
Random forest (RF) regression model is used to predict the lattice constant, magnetic moment and formation energies of full Heusler alloys, half Heusler alloys, inverse Heusler alloys and quaternary Heusler alloys based on existing as well…
We report that special care is needed when longitudinal magnetic susceptibility is computed in a magnetically ordered phase, especially in metals. We demonstrate this by studying static susceptibility in both a ferromagnetic and an…
We numerically study the magnetization and the dispersion relation of a frustrated quantum spin system. Our method, which is named the stochastic state selection method, is a kind of Monte Carlo method to give eigenstates of the system…
Element-specific spectroscopies using synchrotron-radiation can provide unique insights into materials properties. The recently developed technique of X-ray detected ferromagnetic resonance (XFMR) allows studying the magnetization dynamics…
The ultrafast manipulation of magnetic order due to optical excitation is governed by the intricate flow of energy and momentum between the electron, lattice and spin subsystems. While various models are commonly employed to describe these…
We calculate the structural, electronic, and magnetic properties of MnO from first principles, using the full-potential linearized augmented planewave method, with both local-density and generalized-gradient approximations to exchange and…
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…
We report studies of the magnetic properties of a staggered stacked triangular lattice Ba$_2$MnTeO$_6$ using magnetic susceptibility, specific heat, neutron powder diffraction and inelastic neutron scattering measurements, as well as first…
Although magnetic frustration in metals provides a promising avenue for novel quantum phenomena, their microscopic interpretation is often challenging. Here we use the face-centered cubic intermetallic HoInCu$_4$ as model material to show…
We consider magnetostriction in magnetic materials. Starting from a microscopic lattice model of the magneto-elastic coupling, we derive the continuum magnetostriction Hamiltonian in cubic ferromagnets and antiferromagnets. In ferromagnets,…
In this review, we outline the important results on the resistivity encountered by an electron in magnetically ordered materials. The mechanism of the collision between the electron and the lattice spins is shown. Experiments on the spin…
We study a natural conjecture regarding ferromagnetic ordering of energy levels in the Heisenberg model which complements the Lieb-Mattis Theorem of 1962 for antiferromagnets: for ferromagnetic Heisenberg models the lowest energies in each…
Increasingly large datasets of microscopic images with atomic resolution facilitate the development of machine learning methods to identify and analyze subtle physical phenomena embedded within the images. In this work, microscopic images…
The advent of computational statistical disciplines, such as machine learning, is leading to a paradigm shift in the way we conceive the design of new compounds. Today computational science does not only provide a sound understanding of…
We demonstrate a combination of computational tools and experimental 4D-STEM methods to image the local magnetic moment in antiferromagnetic Fe$_2$As with 6 angstrom spatial resolution. Our techniques utilize magnetic diffraction peaks,…
In this paper we present a detailed study of the antiferromagnetic classical Heisenberg model on a bilayer honeycomb lattice in a highly frustrated regime in presence of a magnetic field. This study shows strong evidence of entropic…
Machine learning potentials have emerged as a powerful tool to extend the time and length scales of first principles-quality simulations. Still, most machine learning potentials cannot distinguish different electronic spin orientations and…
We use the state-of-the-arts density-functional-theory method to study various magnetic orders and their effects on the electronic structures of the FeSe. Our calculated results show that, for the spins of the single Fe layer, the striped…
Given the scarcity of experimentally confirmed magnetic structures, the reliable prediction of magnetic ground states is crucial; however, it remains a long-sought challenge because of the complex magnetic potential energy landscape. Here,…
Antiferromagnets are magnetically ordered materials which exhibit no net moment and thus are insensitive to magnetic fields. Antiferromagnetic spintronics aims to take advantage of this insensitivity for enhanced stability, while at the…