Data-driven Design of Novel Materials and Interfaces Enabling Future Technologies

Every technology is intimately connected to a certain materials platform. Information technology is based
on silicon, modern batteries are made from lithium compounds, and magnetic materials are important for
the energy sector. Moreover, interfaces between materials are often the enabler of dedicated
functionalities calling for not only the design of individual materials but also of their interfaces.
The Dresden-concept group “Autonomous Materials Thermodynamics – AutoMaT” leverages state of the
art predictive computational methods for materials and interface design. We specifically focus on the
data-driven discovery of novel two-dimensional (2D) materials for future electronics and energy
applications with strong partners from the DFG collaborative research center 1415 “Synthetic Two-dimensional
Materials” hosted at TU Dresden, HZDR, Forschungszentrum Jülich, and Duke University
(United States).
Two-dimensional materials are traditionally derived from bulk layered compounds. The recent surprising
experimental realization of some 2D sheets obtained from non-layered crystals foreshadows a new
direction for this diverse class of nanostructures. Generalizing these findings, we recently predicted by
data-driven methods and autonomous ab initio calculations a large set of novel representatives. They
exhibit appealing magnetic properties enabling spintronics. These systems and their interfaces are thus an
attractive platform for fundamental and applied nanoscience.