Integrated Computational Engineering of High-performance Materials

NAISS 2024/5-190


NAISS Medium Compute

Principal Investigator:

Pavel Korzhavyi


Kungliga Tekniska högskolan

Start Date:


End Date:


Primary Classification:

20506: Metallurgy and Metallic Materials

Secondary Classification:

10402: Physical Chemistry

Tertiary Classification:

10304: Condensed Matter Physics



The purpose of this application is to allocate supercomputer resources for continuing the research studies in Computational Materials Science that have been conducted under several projects funded by SSF, Vinnova, CCT, and EU during 2014-2023 (SNIC 2014/11-25 -- 2023/5-84) and for new research projects supported by the Swedish Nuclear Waste and Management Company (SKB) and European Institute of Innovation and Technology (EIT RawMaterials, co-funded by the EU): • Structure and Mobility of Defects in Copper (continuation) 2024. Funding source: Swedish Nuclear Fuel and Waste Management Company SKB; • Exploration of deep learning in LIBS analysis for Enhanced Steel Production Processes (WISE-WASP-01-08) 2024. Funding source: Knut and Alice Wallenberg Foundation; • ExpSkills-REM: Expanding Knowledge and Skills in Rare Earth Permanent Magnets Value Chain (Grant no. 21104) 2022 - 2025. Funding source: EIT RawMaterials, co-funded by the EU. The computational studies have focus on lattice defects (point defects, interfaces) and other types of disorder (vibrational, electronic, magnetic) in multicomponent metal alloys, refractory ceramics, and compounds intended for uses in functional materials (transition and rare-earth element (REE) oxides, hydrides, or hydroxides). The computations will continue the research lines of previous projects conducted during 2014-2023 : (i) Impurities in the bulk, at grain boundaries, and open surfaces of copper; (ii) Thermodynamic modeling of multicomponent Fe-Cr-Ni-based alloys (steels, superalloys) using machine learning; and (iii) Thermal disorder in refractory ceramics. Practical importance is due to the decisive influence of intrinsic defects, impurities, and their associates on mechanical properties of materials. Scientific goal of the project is to uncover the atomic mechanisms of such influence through atomistic simulations performed on supercomputers. The simulations are dynamical, to take thermally-activated degrees of freedom into account when computing the free energy and other thermodynamic properties of the considered materials. New material designs are needed in connection with global challenges (climate issues, nature pollution, criticality of raw materials, etc.) that set new requirements on materials' composition and manufacturing processes. The systems under study in the continuation of this project are container materials for spent nuclear fuel, advanced steels, materials for cutting and drilling tools, and high-performance magnets for electric motors and generators. Some of these systems have been investigated experimentally [1-3] and theoretically [4-6]. However, updated property data and models are needed in order to predict the behavior of materials under the conditions that are outside the ranges considered before. Here the guidance from ab initio simulations is extremely valuable. References [1]. T. Ikäläinen, T. Saario, Z. Que, Technical Report SKB TR-22-05 (Svensk Kärnbränslehantering AB, 2022). [2]. X. Yue, et al., Corr. Sci. 210, 110833 (2023). [3]. H. Sepehri-Amin et al., in Handbook of Magnetic Materials, Volume 27 (Elsevier, 2018), pp. 269-372. [4]. C. Lousada, P. Korzhavyi, Materials Today Communications 33, 104281 (2022). [5]. C. Lousada , P. Korzhavyi, J. Mater. Sci. 58, 17004-17018 (2023). [6]. E. Smirnova, M. Nourazar, P.A. Korzhavyi, , Phys. Rev. B. 109, L060103 (2024).