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 2014-2025 (SNIC 2014/11-25 -- 2025/5-316) and for new research projects financed by the Swedish Nuclear Waste and Management Company (SKB), Sweden's Innovation Agency Vinnova, and Swedish Radiation Safety Authority SSM: • Structure and Mobility of Defects in Copper (continuation) 2026. Funding source: SKB; • SELMA - Sustainable ELectrical MAchines, 2025-2026. Funding source: Vinnova; • Diffusion of volatile fission products on accident tolerant fuel – DiVFuel, Funding source: SSM; • Träcellulosa för uppfångning av jod vid oavsiktliga utsläpp - ICell, Funding source: SSM. The computational studies focus on point defects, interfaces, and other types of disorder (vibrational, electronic, magnetic) in multicomponent metals, ceramics, and compounds used as functional materials (transition metal (TM) and rare-earth element (REE) oxides and salts). The computations will continue the research lines of previous projects conducted during 2014-2025: (i) Point defects and cluster in the bulk and at interfaces of copper; (ii) Thermodynamic modeling of multicomponent alloys (steels, lightweight alloys, superalloys, phosphate and oxide minerals) employing Machine Learning approaches; and (iii) Thermal disorder in graphite and refractory carbides. Practical importance is related to the decisive influence of defects 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 into account thermally-activated degrees of freedom 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 [1-4] and theoretically [2-8]. 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]. J. Hagström, R. Sandström and C. M. Lousada, J. Mater. Sci. 60, 25614 (2025). [3]. S. Sinha, D. Kühn, F.O.L. Johansson, A. Lindblad, N. Mårtensson, B. Johansson, P.A. Korzhavyi, A. Föhlisch, Scientific Reports 15(1), 26411 (2025). [4]. J. Liu, Y. Das, P. Korzhavyi et al., Scripta Mater. 265, 116760 (2025). [5]. E. Smirnova, M. Nourazar, P.A. Korzhavyi, Phys. Rev. B. 109, L060103 (2024). [6]. C. Lousada, P. Korzhavyi, Applied Sciences 15, 3306 (2025). [7]. M. Nourazar, P. A. Korzhavyi, Phys. Rev. Materials 9(10), 103404 (2025). [8]. M. Nourazar, Comput. Mater. Sci. 262, 114388 (2026).