Title:	Integrated Computational Engineering of High-performance Materials
DNr:	NAISS 2025/5-316
Project Type:	NAISS Medium Compute
Principal Investigator:	Pavel Korzhavyi <pavelk@kth.se>
Affiliation:	Kungliga Tekniska högskolan
Duration:	2025-06-01 – 2026-06-01
Classification:	20506 10402 10304
Homepage:	https://www.mse.kth.se/properties/materials-technology
Keywords:

Abstract

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) 2025. Funding source: Swedish Nuclear Fuel and Waste Management Company SKB; • Atomic Scale Investigation of Defects in High-Performance Materials, PI: Mehdi Nourzar, 2025. Funding source: Jernkontoret; • 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; • ExpSkills-REM.SPEED: Fast-track extension of project "Expanding Knowledge and Skills in Rare Earth Permanent Magnets Value Chain", year 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 or in their precursors (transition and rare-earth element (REE) oxides and salts). The computations will continue the research lines of previous projects conducted during 2014-2024: (i) Point defects and their associates in the bulk, at grain boundaries, and open surfaces of copper; (ii) Thermodynamic modeling of multicomponent alloys (steels, light-weight alloys, superalloys, phosphate-based minerals) involving machine learning approaches; and (iii) Thermal disorder in graphite and refractory carbides. Practical importance is due to the decisive influence of defects and disorder upon the functional 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 constraints on materials' composition and manufacturing processes. The systems under study are container materials for spent nuclear fuel, advanced steels, refractory alloys, and high-performance functional materials. Some of these systems have been investigated experimentally [1-2] and theoretically [3-5]. Extended 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]. C. Lousada, P. Korzhavyi, J. Mater. Sci. 58, 17004-17018 (2023). [4]. E. Smirnova, M. Nourazar, P.A. Korzhavyi, , Phys. Rev. B. 109, L060103 (2024). [5]. C. Lousada, P. Korzhavyi, Applied Sciences 15, 3306 (2025).