High entropy alloys for advanced nuclear applications

NEA Expert Group on Innovative Structural Materials (EGISM) workshop with the Spanish Center for Energy, Environmental and Technological Research (CIEMAT), 19-21 October 2021

High Entropy Alloys are a promising option for advanced nuclear applications. Their composition can be tuned over a wide range of possibilities to optimise high-temperature mechanical properties, radiation and corrosion resistance, and obtain improved performances compared to conventional materials. However, current knowledge of high-entropy alloys properties is still less advanced compared with conventional alloys and further studies are needed to assess the opportunities they offer.

The NEA Expert Group on Innovative Structural Materials (EGISM) organised a workshop together with the Spanish Center for Energy, Environmental and Technological Research (CIEMAT) on the development, potential uses, opportunities and limitations of high entropy alloys for nuclear applications. Held virtually on 19-21 October 2021, the event attracted 120 participants from 11 countries who exchanged the latest developments and innovations in the field of high entropy materials and complex concentrated alloys.

The workshop opened with an overview on research and development initiatives in this field with perspectives from the People’s Republic of China, the European Union and the United States. The discussions then addressed numerical design and computational approaches to develop high entropy alloys, as well as fabrication and manufacturing and microstructures and mechanical properties of high entropy alloys. Irradiation resistance of high entropy alloys and their compatibility with corrosive environments were also explored.

Participants agreed on the importance of collaboration at the international level to support the acceleration of high entropy materials development for use in the nuclear industry. A broad consensus was also expressed on the need to accumulate both theoretical and experimental data on the behaviour of these materials in conditions that simulate nuclear reactor conditions.

Considering the broad variety of systems included in this class of materials, efforts will be also needed to collect and systematise data in a consistent way as they are produced – especially considering the fact that research in this field heavily involves the use of machine learning techniques for both material design and material modelling purposes.

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