Understanding Interfaces of Hybrid Materials with Machine Learning

The illustration shows the strongly different surface structures that form for the three molecules studied when adsorbed on a metal surface © Jeindl - TU Graz By Susanne Eigner - Using machine learning methods, researchers at TU Graz can predict the structure formation of functionalized molecules at the interfaces of hybrid materials. Now they have also succeeded in looking behind the driving forces of this structure formation. The production of nanomaterials involves self-assembly processes of functionalized (organic) molecules on inorganic surfaces. This combination of organic and inorganic components is essential for applications in organic electronics and other areas of nanotechnology. Until now, certain desired surface properties were often achieved on a trial-and-error basis. Molecules were chemically modified until the best result for the desired surface property was found. However, the processes controlling the self-assembly of molecules at interfaces are so complex that small molecular changes can lead to completely different motifs.