New hard magnets free of rare earth metals

© Fraunhofer IWM
Magnetic spin polarization at a grain boundary in a ferromagnetic metal on the atomistic scale.

Hard magnets play a crucial role in converting electromechanical energy in electromobility applications and wind turbines. The increased demand for materials containing rare earth metals has, however, reached a critical level. In the search for material substitutes that are free of rare earth metals, ab initio density functional theory is used to calculate magnetic parameters for real and hypothetical crystal phases. “High throughput screening“ material theory and “Data Mining“ information theory are used in simulations to predict the most promising candidates from thousands of magnetic phases.

The web app MagnetPredictor (in German) was developed at the Fraunhofer IWM to demonstrate the benefit of modern Machine Learning techniques for the prediction of magnetic properties. For (hypothetic) intermetallic phases, a quick rough estimate of these properties can be generated for arbitrary chemical compositions.

Fraunhofer IWM Video Series: Atomistic Simulations

Dr. Daniel Urban

How do atomistic simulations facilitate the substitution of critical elements within a material?

Further Information



  • Krugel, G.; Körner, W.; Urban, D.F.; Gutfleisch, O.; Elsässer, C., High-throughput screening of rare-earth-lean intermetallic 1-13-X compounds for good hard-magnetic properties, Metals 9/10 (2019) 1096 1-13 Link
  • Körner, W.; Krugel, G.; Urban, D.F.; Elsässer, C., Screening of rare-earth-lean intermetallic 1-11 and 1-11-X compounds of YNi9In2-type for hard-magnetic applications, Scripta Materialia 154 (2018) 295-299 Link
  • Möller, J.; Körner, W.; Krugel, G.; Urban, D.F.; Elsässer, C., Compositional optimization of hard-magnetic phases with machine-learning models, Acta Materialia 153 (2018) 53-61 Link
  • Körner, W.; Krugel, G.; Elsässer, C.; Theoretical screening of intermetallic ThMn12-type phases for new hard-magnetic compounds with low rare earth content, Scientific Reports 6 (2016) 24686 1-9; 142/2016 Link
  • Drebov, N.; Martinez-Limia, A.; Kunz, L.; Gola, A.; Shigematsu, T.; Eckl, T.; Gumbsch, P.; Elsässer C.; Ab initio screening methodology applied to the search for new permanent magnetic materials; New Journal of Physics 15 (2013) 125023 1-24 Link

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