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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…

Materials Science · Physics 2018-10-04 Johannes J. Möller , Wolfgang Körner , Georg Krugel , Daniel F. Urban , Christian Elsässer

Complex magneto structural behaviour of rare rich intermetallic Tb$_3$Co is reported in this study. Below the 84K (T$_N$), it undergoes a first order magnetic transition 72K confirmed from specific heat and magnetization measurements.…

Materials Science · Physics 2019-08-23 Srikanta Goswami , P. D. Babu , R. Rawat

It is demonstrated that the magnetic interactions can be drastically different for nano-sized systems compared to those of bulk or surfaces. Using a real-space formalism we have developed a method to calculate non-collinear magnetization…

We propose an approach for exploring magnetic structures by using Liechtenstein's method for exchange couplings from the results of first-principles calculations. Our method enables efficient and accurate exploration of stable magnetic…

Materials Science · Physics 2025-05-26 Taro Fukazawa , Haruki Okumura , Tetsuya Fukushima , Hisazumi Akai , Takashi Miyake

An exciting development over the past few decades has been the use of high-throughput computational screening as a means of identifying promising candidate materials for a variety of structural or functional properties. Experimentally, it…

Materials Science · Physics 2020-02-12 Christina A. C. Garcia , Joshua D. Bocarsly , Ram Seshadri

The structural and magnetic properties of functional Ni-Mn-Z (Z = Ga, In, Sn) Heusler alloys are studied by first-principles and Monte Carlo methods. The \textit{ab initio} calculations give a basic understanding of the underlying physics…

We present a first-principles approach for the computation of the magnetic Gibbs free energy of materials using magnetically constrained supercell calculations. Our approach is based on an adiabatic approximation of slowly varying local…

Materials Science · Physics 2022-02-24 Eduardo Mendive-Tapia , Jörg Neugebauer , Tilmann Hickel

We propose a new ab initio method designed for the accurate calculation of effective exchange integrals between atoms with numerous open-shells. This method applies to ferromagnetic as well as antiferromagnetic exchange, direct or…

Strongly Correlated Electrons · Physics 2015-05-13 Alain Gellé , Julien Varignon , Marie-Bernadette Lepetit

The recent observation of ferromagnetic order in two-dimensional (2D) materials has initiated a booming interest in the subject of 2D magnetism. In contrast to bulk materials, 2D materials can only exhibit magnetic order in the presence of…

Materials Science · Physics 2020-02-18 Daniele Torelli , Kristian S. Thygesen , Thomas Olsen

Altermagnets (AM) are a novel class of magnetic materials with zero net magnetization but broken time-reversal symmetry and spin-split bands exceeding the spin-orbit coupling scale, offering unique control of individual spin-channel and…

Materials Science · Physics 2024-12-16 Xuhao Wan , Subhasish Mandal , Yuzheng Guo , Kristjan Haule

Magnetic materials have been applied in a large variety of technologies, from data storage to quantum devices. The development of 2D materials has opened new arenas for magnetic compounds, even when classical theories discourage their…

Materials Science · Physics 2022-02-11 Carlos Mera Acosta , Elton Ogoshi , Jose Antonio Souza , Gustavo M. Dalpian

Magnetic structures of the noncentrosymmetric magnet Sr$_2$MnSi$_2$O$_7$ were examined through neutron diffraction for powder and single-crystalline samples, as well as magnetometry measurements. All allowed magnetic structures under the…

Strongly Correlated Electrons · Physics 2024-10-08 Y. Nambu , M. Kawamata , X. Pang , H. Murakawa , M. Avdeev , H. Kimura , H. Masuda , N. Hanasaki , Y. Onose

Magnetic structures, which play a central role in determining their physical properties, are known for only very limited compounds. Traditional theoretical approaches to predicting magnetic structures predominantly rely on first-principles…

Multicomponent Heusler alloys exhibit various magnetic properties arising from their diverse atomic compositions and crystal structures. Identifying the general physical principles that govern these behaviors is essential for advancing…

Materials Science · Physics 2026-02-10 Zhenyang Xie , Jitong Song , Yuntao Wu , Yuanji Xu , Fuyang Tian

Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of…

We construct asymptotic arguments for the relative efficiency of rejection-free Monte Carlo (MC) methods compared to the standard MC method. We find that the efficiency is proportional to $\exp{({const} \beta)}$ in the Ising, $\sqrt{\beta}$…

Statistical Mechanics · Physics 2009-11-11 H. Watanabe , S. Yukawa , M. A. Novotny , N. Ito

Important phenomena such as magnetostriction, magnetocaloric, and magnetoelectric effects arise from, or could be enhanced by, the coupling of magnetic and structural degrees of freedom. The coupling of spin and lattice also influence…

Materials Science · Physics 2021-03-25 Luis Casillas-Trujillo , Rickard Armiento , Björn Alling

Prediction and characterization of crystal structures of alloys are a key problem in materials research. Using high-throughput ab initio calculations we explore the low-temperature phase diagrams for the following systems: {Bi-In, Bi-Mg,…

Materials Science · Physics 2007-05-23 Stefano Curtarolo , Aleksey N. Kolmogorov , Franklin Hadley Cocks

Owing to their favorable scaling with dimensionality, Monte Carlo (MC) methods have become the tool of choice for numerical integration across the quantitative sciences. Almost invariably, efficient MC integration schemes are strictly…

Statistical Mechanics · Physics 2010-01-29 Artur B. Adib

Nearest-neighbor Heisenberg antiferromagnet on a face-centered cubic lattice is studied by extensive Monte Carlo simulations in zero magnetic field. The parallel tempering algorithm is utilized, which allows to overcome a slow relaxation of…

Statistical Mechanics · Physics 2007-05-23 M. V. Gvozdikova , M. E. Zhitomirsky