This research group focus on computational design of crystalline materials for applications in a sustainable society. Materials form an integral part of modern society, from solar cells and batteries to catalysts and building materials. However, discovery of new materials is a slow process, and application of computational methods and artificial intelligence holds potential to accelerate materials discovery. In the computational materials chemistry group led by Assistant Professor Kasper Tolborg, we develop and apply novel computational methods based on quantum chemistry and artificial intelligence to accelerate materials design and gain deeper understanding of materials properties. We are particularly interested in the effects of entropy and disorder on the properties and stability of materials, and how tailored disorder can be used as a tool to improve materials properties. The research group focus on the following areas:

• Solid electrolytes for next-generation batteries
• Hybrid organic-inorganic ferro- and piezoelectric materials
• Fundamentals of entropy and disorder in crystals
• Machine learning methods for accelerated materials design

More information about the Computational Materials Chemistry group here.