Static Distortion Waves in Epitaxial Non-Commensurate Adlayers

• Applicant: Professor Dr. Torsten Fritz
• Subject Area: Experimental Condensed Matter Physics
• Term: from 2019 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 430865859

The main scientific goal of our proposal is to demonstrate that static distortion waves (SDWs) play a universal role in the structure formation of organic adsorbates. These represent rather flexible adsorbate lattices caused by the weak interaction forces between molecules, namely van der Waals forces and – if suitable atoms are contained in the molecules – hydrogen bonds. To that end, we will investigate self-assembled monolayers of a variety of molecules with several distinct aspects, grown on graphitic and metallic substrates. A unique method is proposed to quantitatively assess interactions in two-dimensional non-commensurate molecular aggregates (which exhibit a broad distribution of nearest-neighbor distances) via the observation of SDWs by means of low-temperature STM accompanied by distortion-corrected LEED measurements. To rationalize the experimental results, relaxation simulations (away from the average lattice) will be performed. The parameter-free intra- and interlayer interaction energy landscapes needed for those simulations will be obtained from state-of-the-art dispersion-corrected DFT calculations.From a computational/theoretical point of view, SDWs are particularly interesting for multiple reasons. Importantly, in SDW systems molecules adsorb on a variety of different adsorption sites. To describe SDWs, it is thus insufficient to only reproduce quantitatively the energetically most favorable adsorption site. Rather, it is imperative to obtain a good representation of a large part of the potential energy surfaces describing the molecule-substrate and molecule-molecule interactions. As a first step, we will map those interactions separately by discretizing and “brute-forcing” the potential energy surfaces. Going beyond the established approach, we will test a number of different computational methods for the evaluation of molecule-substrate and molecule-molecule interactions. As a second step, we will speed up the evaluation of the potential energy surfaces using machine learning methods. Specifically, we will rely on Gaussian Process Regression (GPR) to determine interactions at the interface of organic molecules with inorganic substrates. By combining the experimental and calculation results, quantitative information on the strength of the intermolecular interactions will be obtained.

• DFG Programme: Research Grants
• International Connection: Austria
• Co-Investigator: Dr. Roman Forker
• Cooperation Partner: Professor Oliver T. Hofmann, Ph.D.