Electronic theory of materials properties: from fundamental understanding towards materials design
||Electronic theory of materials properties: from fundamental understanding towards materials design|
||SNIC Large Compute|
||Igor Abrikosov <firstname.lastname@example.org>|
||2019-07-01 – 2020-07-01|
Within this project, we will focus on studies of stable and metastable materials broadly varying internal and external parameters, like crystal structure, pressure, temperature and composition. Combining theory with experiment, we will discover new phases and characterize their properties. We will obtain fundamental understanding of the physical principles behind the formation of metastable structures and use it for the knowledge-based design of novel materials with exciting properties attractive for advanced scientific and technological applications. At SNIC 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 or DESY. We will address most challenging applications, relevant e.g. for quantum technology, hard-coatings, low-dimensional materials for supercapacitors, and for many other applications.
The project will be organized in the form of several activities, corresponding to our on-going research supported by VR, VINNOVA, SSF, KAW (including 2 new KAW projects), SFOs AFM and SeRC. The activities for the period from 19-07-01 until 20-06-30 include:
A1. Materials at extreme conditions: discovering fundamental relationships to accelerate knowledge-based design (on-going VR project)
A2. Wide-bandgap semiconductors for the next generation of quantum devices (new KAW project).
A3. Fundamental understanding of metastable states of matter for advanced materials design (new KAW Scholar project).
A4. Theoretical support for materials design of functional surfaces for cutting tools, fuel cells, and batteries (VINNOVA project).
A5. Multifunctional 2D materials (MXenes) for energy storage (SSF project).
A6. Data-driven computational materials design (SFO SeRC project).
A7. Point defect properties of Ga2O3 (SFO AFM project).