Computational Design of Rare-Earth Reduced Permanent Magnets

Multiscale simulation is a key research tool in the quest for new permanent magnets. Starting with first principles methods, a sequence of simulation methods can be applied to calculate the maximum possible coercive field and expected energy density product of a magnet made from a novel magnetic mat...

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Main Authors: Alexander Kovacs, Johann Fischbacher, Markus Gusenbauer, Harald Oezelt, Heike C. Herper, Olga Yu. Vekilova, Pablo Nieves, Sergiu Arapan, Thomas Schrefl
Format: Article
Language:English
Published: Elsevier 2020-02-01
Series:Engineering
Online Access:http://www.sciencedirect.com/science/article/pii/S2095809919308689
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author Alexander Kovacs
Johann Fischbacher
Markus Gusenbauer
Harald Oezelt
Heike C. Herper
Olga Yu. Vekilova
Pablo Nieves
Sergiu Arapan
Thomas Schrefl
author_facet Alexander Kovacs
Johann Fischbacher
Markus Gusenbauer
Harald Oezelt
Heike C. Herper
Olga Yu. Vekilova
Pablo Nieves
Sergiu Arapan
Thomas Schrefl
author_sort Alexander Kovacs
collection DOAJ
description Multiscale simulation is a key research tool in the quest for new permanent magnets. Starting with first principles methods, a sequence of simulation methods can be applied to calculate the maximum possible coercive field and expected energy density product of a magnet made from a novel magnetic material composition. Iron (Fe)-rich magnetic phases suitable for permanent magnets can be found by means of adaptive genetic algorithms. The intrinsic properties computed by ab initio simulations are used as input for micromagnetic simulations of the hysteresis properties of permanent magnets with a realistic structure. Using machine learning techniques, the magnet’s structure can be optimized so that the upper limits for coercivity and energy density product for a given phase can be estimated. Structure property relations of synthetic permanent magnets were computed for several candidate hard magnetic phases. The following pairs (coercive field (T), energy density product (kJ·m−3)) were obtained for iron-tin-antimony (Fe3Sn0.75Sb0.25): (0.49, 290), L10-ordered iron-nickel (L10 FeNi): (1, 400), cobalt-iron-tantalum (CoFe6Ta): (0.87, 425), and manganese-aluminum (MnAl): (0.53, 80). Keywords: Rare-earth, Permanent magnets, Micromagnetics
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spelling doaj.art-3e518bedb17e40aca524e65934fc3e932022-12-21T18:41:34ZengElsevierEngineering2095-80992020-02-0162148153Computational Design of Rare-Earth Reduced Permanent MagnetsAlexander Kovacs0Johann Fischbacher1Markus Gusenbauer2Harald Oezelt3Heike C. Herper4Olga Yu. Vekilova5Pablo Nieves6Sergiu Arapan7Thomas Schrefl8Department for Integrated Sensor Systems, Danube University Krems, Wiener Neustadt 2700, AustriaDepartment for Integrated Sensor Systems, Danube University Krems, Wiener Neustadt 2700, AustriaDepartment for Integrated Sensor Systems, Danube University Krems, Wiener Neustadt 2700, AustriaDepartment for Integrated Sensor Systems, Danube University Krems, Wiener Neustadt 2700, AustriaDepartment of Physics and Astronomy, Uppsala University, Uppsala 75120, SwedenDepartment of Physics and Astronomy, Uppsala University, Uppsala 75120, SwedenInternational Research Centre in Critical Raw Materials for Advanced Industrial Technologies, University of Burgos, Burgos 09001, Spain; IT4Innovations, VŠB-Technical University of Ostrava, Ostrava-Poruba 70833, Czech RepublicInternational Research Centre in Critical Raw Materials for Advanced Industrial Technologies, University of Burgos, Burgos 09001, Spain; IT4Innovations, VŠB-Technical University of Ostrava, Ostrava-Poruba 70833, Czech RepublicDepartment for Integrated Sensor Systems, Danube University Krems, Wiener Neustadt 2700, Austria; Corresponding author.Multiscale simulation is a key research tool in the quest for new permanent magnets. Starting with first principles methods, a sequence of simulation methods can be applied to calculate the maximum possible coercive field and expected energy density product of a magnet made from a novel magnetic material composition. Iron (Fe)-rich magnetic phases suitable for permanent magnets can be found by means of adaptive genetic algorithms. The intrinsic properties computed by ab initio simulations are used as input for micromagnetic simulations of the hysteresis properties of permanent magnets with a realistic structure. Using machine learning techniques, the magnet’s structure can be optimized so that the upper limits for coercivity and energy density product for a given phase can be estimated. Structure property relations of synthetic permanent magnets were computed for several candidate hard magnetic phases. The following pairs (coercive field (T), energy density product (kJ·m−3)) were obtained for iron-tin-antimony (Fe3Sn0.75Sb0.25): (0.49, 290), L10-ordered iron-nickel (L10 FeNi): (1, 400), cobalt-iron-tantalum (CoFe6Ta): (0.87, 425), and manganese-aluminum (MnAl): (0.53, 80). Keywords: Rare-earth, Permanent magnets, Micromagneticshttp://www.sciencedirect.com/science/article/pii/S2095809919308689
spellingShingle Alexander Kovacs
Johann Fischbacher
Markus Gusenbauer
Harald Oezelt
Heike C. Herper
Olga Yu. Vekilova
Pablo Nieves
Sergiu Arapan
Thomas Schrefl
Computational Design of Rare-Earth Reduced Permanent Magnets
Engineering
title Computational Design of Rare-Earth Reduced Permanent Magnets
title_full Computational Design of Rare-Earth Reduced Permanent Magnets
title_fullStr Computational Design of Rare-Earth Reduced Permanent Magnets
title_full_unstemmed Computational Design of Rare-Earth Reduced Permanent Magnets
title_short Computational Design of Rare-Earth Reduced Permanent Magnets
title_sort computational design of rare earth reduced permanent magnets
url http://www.sciencedirect.com/science/article/pii/S2095809919308689
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