Multicomponent metal alloys without the main element, called medium-entropy alloys or high-entropy alloys depending on the number of constituent elements, have been recognized as promising functional materials in the last two decades, which are of great importance in materials science due to several unique properties. These materials are very attractive for a wide range of the most demanding practical applications, such as energy storage and conversion, nuclear power, and biomedical applications. Therefore, their development and improvement will ensure a great impact on the development of industry and technology in the future and, in particular, on the implementation of the goals of the European Green Course and the achievement of the goals of European sustainable development. In this project, we aim to develop and apply an original methodology based on atomistic modeling and machine learning methods for X-ray absorption spectroscopy of multicomponent alloys at the atomic level to better understand the effects of short-range order and chemical composition on alloy formation and properties. The project is compliant with the Research and Innovation Strategies for Smart Specialisation (RIS3) of Latvia in the area of "Smart materials, technologies and engineering systems".

Results

Publications:

1. A. Smekhova, D. Gaertner, A. Kuzmin, A. Guilherme Buzanich, G. Schuck, I. Zizak, G. Wilde, K. V. Yusenko, S. Divinski,
   Anomalies in the short-range local environment and atomic diffusion in single crystalline equiatomic CrMnFeCoNi high-entropy alloy,
   Nano Res. 17 (2024) 5336-5348.
   Open Access
   


2. S. Drescher, A. Kuzmin, E. Welter, J. Freudenberger, A. Smekhova,
   Component-dependent lattice distortions and atomic scale insights in multi-component Au-Cu-Ni-Pd-Pt based alloys,
   Nano Res. 18 (2025) 94907122.
   Open Access