Criticality of Rare Earth Elements

Project description

Rare earth elements are an indispensable raw material for the manufacture of cell phones, laptops, electric motors, and wind turbines. Motors for electric vehicles and generators for wind power plants in particular require powerful permanent magnets that contain rare earth elements such as neodymium and dysprosium. In view of the critical supply situation and rising prices, which are due in no small part to China's dominant market position, a consortium of seven Fraunhofer Institutes has initiated the Fraunhofer flagship project KSE (Criticality of Rare Earth Elements) to ensure a resource-efficient supply of high-performance materials for permanent magnets to industry.

The aim of the project was to reduce the specific primary demand for heavy rare earth elements by 2017. The research team investigated various approaches, including the search for substitute materials, the optimization of manufacturing processes and production technologies for permanent magnets, and the development of concepts for recycling used electric motors. For demonstration purposes, two electric motors (a simple small electric drive and a complex traction motor) were manufactured from magnetic materials containing a lower proportion of neodymium and dysprosium. This was the first time that the entire process chain, from the theoretical prediction of new magnetic materials to a practical electric motor, had been mapped. In addition, a dynamic market model was developed to better calculate risks and environmental influences. 

Fraunhofer IWM subproject:

As part of the joint project, Fraunhofer IWM used computational screening simulations to search for novel intermetallic phases with good hard magnetic properties. To search for SE-free material substitutes, ab initio density functional theory was used to calculate magnetic parameters for real and hypothetical crystal phases. Using material-theoretical high-throughput screening and information-theoretical data mining, promising candidates were predicted from thousands of magnetic phases. The MagnetPredictor web application (Magnet Predictor RETM12X) developed at Fraunhofer IWM demonstrates the usefulness of modern machine learning methods for predicting the magnetic properties of (virtual) intermetallic compounds with arbitrary chemical compositions.

For more information, see, for example:

• 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
• 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