The impact of the atomic structure of an interface on its electronic and mechanical properties

Organic adlayers on inorganic substrates often display unique properties. These properties depend, apart from the chemical composition, on the structure of the adlayer. Yet, due to the enormous number of possible surface interface structures, is not feasible to use conventional stochastic algorithms for the identification of structures with desirable properties.

To overcome this challenge, we coarse grain the search space and combine Bayesian machine-leaning with first-principles electronic-structure modeling. This allows considering structures containing up to 100 molecules per unit cell and enables predicting properties such as formation energies, work functions, coherent fractions (obtained via X-ray standing wave measurements) as well as shear forces.

Our approach enables investigating dense-packed interface structures, with good agreement with experiment. We generate insight into how the interactions at the interface impact the formation of different structural motifs and gauge the impact of thermodynamic conditions on the interface structure and its properties. Moreover, we perform geometry optimisation of large-scale interface structures to study the formation of static distortion waves and their impact on the frictional properties of the interface. As an outlook, we discuss how to account for dynamical processes at interfaces, where we focus on the study of energy dissipation as a result of electronic and photonic excitations.

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