Within this project, we will model materials and simulate phenomena relevant for fundamental science and for advanced applications, ranging from hard coatings for cutting tools to wide-band gap semiconductors for the next generation of quantum devices. Combining theory with experiment, we will find materials solutions for nanoscale quantum sensing and design advanced multiple principal element alloys with attractive mechanical properties. We will develop tools for data-driven materials design and transfer the knowledge to academia and industry.
The main aim of our research is to deepen fundamental understanding of materials properties from the basic principles of quantum mechanics. At NAISS supercomputers, we will use efficient tools for materials modeling to guide and support materials design. Our simulations will be relevant for interpretation of experiments at large-scale facilities, like the MAX IV lab. We will address most challenging applications, relevant for several UN Sustainable Development Goals, including Affordable and Clean Energy (7), Industry, Innovation and Infrastructure (9), and Good Health and Well-being (3).
The project is organized in four work-packages (WP), corresponding to our on-going research supported by grants from VR, VINNOVA, KAW, SRA AFM and SeRC, as well as from Olle Engkvists stiftelse. We renew the structure of work packages (WPs) in comparison to the on-going project SNIC 2022/1-6 and formulate multiple novel tasks within each WPs.
WP1. New concept for design of multi-principal elements alloys for advanced applications. Based on improved fundamental understanding of the interplay between formation of metastable phases, their electronic structure, magnetism and lattice vibrations at finite temperature, we propose to explore a possibility to achieve unique flexibility of materials properties by tuning the materials composition towards an immediate vicinity of their thermodynamic and/or dynamic stabilization.
WP2. Materials solutions for nanoscale quantum sensing. We will investigate magneto-optical properties, as well as the longitudinal spin relaxation, decoherence and spin state properties of novel defect-spin qubit centers to quantify their potential for applications.
WP3. Data-driven design of functional materials for hard coating applications. We will generate data for the Hard-coating Alloys Data Base (HADB) developed in collaboration with Sandvic Coromant, explore data correlations and improve the accuracy of AI tools.
WP4. Advanced materials with reduced dimensionality for the next generation energy and electronics applications. We will carry out simulations for novel 2D materials and vdW structures. Importantly, we will explore our novel design concept for design of materials with reduced dimensionality via high-pressure synthesis.
We use HPC resources efficiently and productively. Several new PhD and Postdoctoral positions will be announced soon in our group. This motivates our request to increase our allocation by ~10%.