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Related papers: Computational Design of the Rare-Earth Reduced Per…

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The development of permanent magnets containing less or no rare-earth elements is linked to profound knowledge of the coercivity mechanism. Prerequisites for a promising permanent magnet material are a high spontaneous magnetization and a…

In this work we investigate the potential of tetragonal L1$_0$ ordered FeNi as candidate phase for rare earth free permanent magnets taking into account anisotropy values from recently synthesized, partially ordered FeNi thin films. In…

We employ a combination of machine learning and first-principles calculations to predict magnetic properties of rare-earth lean magnets. For this purpose, based on training set constructed out of experimental data, the machine is trained to…

Materials Science · Physics 2020-09-16 Anita Halder , Samir Rom , Aishwaryo Ghosh , Tanusri Saha-Dasgupta

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

In this paper we perform the detailed numerical analysis of remagnetization processes in nanocomposite magnetic materials consisting of magnetically hard grains (i.e. grains made of a material with a high magnetocrystalline anisotropy)…

Materials Science · Physics 2016-08-29 Sergey Erokhin , Dmitry Berkov

Machine learning was utilized to efficiently boost the development of soft magnetic materials. The design process includes building a database composed of published experimental results, applying machine learning methods on the database,…

The maximum coercivity that can be achieved for a given hard magnetic alloy is estimated by computing the energy barrier for the nucleation of a reversed domain in an idealized microstructure without any structural defects and without any…

Accurate simulations of isotropic permanent magnets require to take the magnetization process into account and consider the anisotropic, nonlinear, and hysteretic material behaviour near the saturation configuration. An efficient method for…

This paper introduces a new approach for simulating magnetic properties of nanocomposites comprising magnetic particles embedded in a non-magnetic matrix, taking into account the 3D structure of the system in which particles' positions…

Mesoscale and Nanoscale Physics · Physics 2014-10-22 R. F. Neumann , M. Bahiana , L. G. Paterno , M. A. G. Soler , J. P. Sinnecker , J. G. Wen , P. C. Morais

Conjugate gradient methods for energy minimization in micromagnetics are compared. When the step length in the line search is controlled, conjugate gradient techniques are a fast and reliable way to compute the hysteresis properties of…

Materials Science · Physics 2017-08-08 J. Fischbacher , A. Kovacs , H. Oezelt , T. Schrefl , L. Exl , J. Fidler , D. Suess , N. Sakuma , M. Yano , A. Kato , T. Shoji , A. Manabe

Increased demand for high-performance permanent magnets in the electric vehicle and wind turbine industries has prompted the search for cost-effective alternatives.Discovering new magnetic materials with the desired intrinsic and extrinsic…

Materials Science · Physics 2024-07-26 Churna Bhandari , Gavin N. Nop , Jonathan D. H. Smith , Durga Paudyal

We developed a micromagnetic method for modeling magnetic systems with periodic boundary conditions along an arbitrary number of dimensions. The main feature is an adaptation of the Ewald summation technique for evaluation of long-range…

Mesoscale and Nanoscale Physics · Physics 2015-10-30 Aleksander L. Wysocki , Vladimir P. Antropov

We demonstrate how micromagnetic simulations can be employed in order to characterize and analyze the magnetic microstructure of nanocomposites. For the example of nanocrystalline Nd$-$Fe$-$B, which is a potential material for future…

Materials Science · Physics 2018-04-04 Sergey Erokhin , Dmitry Berkov , Masaaki Ito , Akira Kato , Masao Yano , Andreas Michels

As a pinning-controlled permanent magnet, tailoring the cellular nanostructure of samarium-cobalt-based 1:7-type (SmCo-1:7) magnets remains crucial for improving magnetic performance. Jointing forward and inverse machine learning models…

A new methodology for micromagnetic simulations of magnetic nanocomposites is presented. The methodology is especially suitable for simulations of two-phase composites consisting of magnetically hard inclusions in a soft magnetic matrix…

Mesoscale and Nanoscale Physics · Physics 2011-09-20 Sergey Erokhin , Dmitry Berkov , Nataliya Gorn , Andreas Michels

Based on a critical analysis of the experimental coercive properties, general considerations on the reversal mechanisms in RFeB magnets are recalled. By plotting together the experimental parameters obtained in various magnets, common…

Materials Science · Physics 2015-02-10 S. Bance , G. Ciuta , T. Shoji , T. Gao , G. Hrkac , M. Yano , A. Manabe , N. M. Dempsey , T. Schrefl , D. Givord

In this work we perform a systematic calculation of the Fe-Ta phase diagram to discover novel hard magnetic phases. By using structure prediction methods based on evolutionary algorithms, we identify two new energetically stable magnetic…

Materials Science · Physics 2020-01-29 Sergiu Arapan , Pablo Nieves , Heike C. Herper , Dominik Legut

We formulated a technique which combines the first-principles, micromagnetic and microstructural calculations and allows us to study the nature of hysteretic phenomena in hard magnets. Two distinct sources of coercivity in polytwinned CoPt…

Materials Science · Physics 2009-11-07 K. D. Belashchenko , V. P. Antropov

Additive manufacturing (AM) offers an unprecedented opportunity for the quick production of complex shaped parts directly from a powder precursor. But its application to functional materials in general and magnetic materials in particular…

Materials Science · Physics 2019-04-02 Min Yi , Bai-Xiang Xu , Oliver Gutfleisch

Solid state theory, density functional theory and its generalizations for correlated systems together with numerical simulations on supercomputers allow nowadays to model magnetic systems realistically and in detail and can be even used to…

Materials Science · Physics 2023-10-16 Vladislav Borisov
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