Data-Driven Discovery of Functional 2D Materials

The development of materials that can lead to new technological advances has traditionally been a slow and expensive process based largely on empiricism. Recently, it has become possible using supercomputers to simulate materials down to the smallest atomic scale and thereby predict the properties of a material with a given chemical composition before it is made in the laboratory. With his VILLUM project, Kristian Thygesen will develop software that combines advanced materials computations with artificial intelligence to enable the design of materials with specific, desired properties more effectively and rationally. The method will be used to search for new types of nano-materials composed of just a few atomic layers (2D materials) that can be used as building blocks for the next generation of electronic components or perhaps future quantum computers.