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The magnetic properties of a material are determined by a subtle balance between the various interactions at play, a fact that makes the design of new magnets a daunting task. High-throughput electronic structure theory may help to explore…

Materials Science · Physics 2019-10-16 James Nelson , Stefano Sanvito

Technologies that function at room temperature often require magnets with a high Curie temperature, $T_\mathrm{C}$, and can be improved with better materials. Discovering magnetic materials with a substantial $T_\mathrm{C}$ is challenging…

Materials Science · Physics 2023-08-09 Joshua F. Belot , Valentin Taufour , Stefano Sanvito , Gus L. W. Hart

Theoretical prediction of the 2nd-order magnetic transition temperature (TM) used to be arduous. Here, we develop a first principle-based, fully automatic structure-to-TM method for two-dimensional (2D) magnets whose effective Hamiltonians…

Materials Science · Physics 2023-12-08 Haichang Lu , Tai Yang , Zhimei Sun , John Robertson , Weisheng Zhao

The Curie temperature ($T_C$) of binary alloy compounds consisting of 3$d$ transition-metal and 4$f$ rare-earth elements is analyzed by a machine learning technique. We first demonstrate that nonlinear regression can accurately reproduce…

Searching the optimal doping compositions of the Y-type hexaferrite Ba2Mg2Fe12O22 remains a long-standing challenge for enhanced non-collinear magnetic transition temperature (TNC). Instead of the conventional trial-and-error approach, the…

We use magnetoresistance measurements at high magnetic field (B \leq 65 T) and low temperature (T \geq 500 mK) to gain fresh insights into the behavior of the upper critical field, Hc2, in superconducting ultrathin FeSe films of varying…

Magnetic materials have a plethora of applications ranging from informatics to energy harvesting and conversion. However, such functionalities are limited by the magnetic ordering temperature. In this work, we performed machine learning on…

Materials Science · Physics 2021-10-06 T. Long , N. M. Fortunato , Yixuan Zhang , O. Gutfleisch , H. Zhang

Machine Learning (ML) has impacted numerous areas of materials science, most prominently improving molecular simulations, where force fields were trained on previously relaxed structures. One natural next step is to predict material…

Materials Science · Physics 2023-11-28 Robin Hilgers , Daniel Wortmann , Stefan Blügel

When exploring new magnetic materials, the effect of alloying plays a crucial role for numerous properties. By altering the alloy composition, it is possible to tailor, e.g., the Curie temperature ($T_\text{C}$). In this work, $T_\text{C}$…

Materials Science · Physics 2024-12-19 Marian Arale Brännvall , Rickard Armiento , Björn Alling

Many frustrated spin models on three-dimensional (3D) lattices are currently being investigated, both experimentally and theoretically, and develop new types of long-range orders in their respective phase diagrams. They present…

Strongly Correlated Electrons · Physics 2023-07-06 M. G. Gonzalez , B. Bernu , L. Pierre , L. Messio

Combining material informatics and high-throughput electronic structure calculations offers the possibility of a rapid characterization of complex magnetic materials. Here we demonstrate that datasets of electronic properties calculated at…

Materials Science · Physics 2017-06-07 Mario Žic , Thomas Archer , Stefano Sanvito

The thermodynamic properties (magnetization, magnetic susceptibility, transverse and longitudinal correlation lengths, specific heat) of one- and two-dimensional ferromagnets with arbitrary spin S in a magnetic field are investigated by a…

Strongly Correlated Electrons · Physics 2009-11-13 I. Juhász Junger , D. Ihle , L. Bogacz , W. Janke

The temperature dependent stability of the magnetic phases of FeRh were investigated by means of total energy calculations with magnetic disorder treated within the uncompensated disordered local moment (uDLM) approach. In addition, Monte…

Materials Science · Physics 2016-02-03 S. Polesya , S. Mankovsky , D. Ködderitzsch , J. Minár , H. Ebert

Much research in recent years has focused on using empirical machine learning approaches to extract useful insights on the structure-property relationships of superconductor material. Notably, these approaches are bringing extreme benefits…

Data Analysis, Statistics and Probability · Physics 2020-02-13 Thanh Dung Le , Rita Noumeir , Huu Luong Quach , Ji Hyung Kim , Jung Ho Kim , Ho Min Kim

An energy based stochastic model for temperature dependent anhysteretic magnetization curves of ferromagnetic materials is proposed and bench marked against experimental data. This is based on the calculation of macroscopic magnetic…

Materials Science · Physics 2016-12-30 Sanjay Sah , Jayasimha Atulasimha

The temperature dependence of electronic and magnetic properties of the organic charge-transfer salt (DOEO)$_4$[HgBr$_4$]TCE was investigated using magnetometry. Electronic transport properties revealed three distinct phases which are…

High-temperature superconductivity occurs in strongly correlated materials such as copper oxides and iron-based superconductors. Numerous experimental and theoretical works have been done to identify the key parameters that induce…

Superconductivity · Physics 2023-05-02 Kota Ido , Yuichi Motoyama , Kazuyoshi Yoshimi , Takahiro Misawa

Recent advancements in spintronics and fundamental physical research have brought increased attention to the rare-earth-based magnetically ordered materials. One of the important properties of these materials is the temperature dependence…

Materials Science · Physics 2025-12-02 Rostyslav O. Serha , Anna Pomyalov , Andrii V. Chumak , Victor S. L'vov

We have studied the magnetocaloric effect (MCE) in the shape-memory Heusler alloy Ni$_{50}$Mn$_{35}$In$_{15}$ by direct measurements in pulsed magnetic fields up to 6 and 20 T. The results in 6 T are compared with data obtained from…

Materials Science · Physics 2015-02-23 M. Ghorbani Zavareh , C. Salazar Mejía , A. K. Nayak , Y. Skourski , J. Wosnitza , C. Felser , M. Nicklas

Refrigeration based on the magnetocaloric effect (MCE) can contribute to energysaving, environmentally friendly cooling in private households, or industrial application. The cooling is based on the reversible heat release or uptake during a…

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