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O: Fachverband Oberflächenphysik

O 4: Tribology: Surfaces and Nanostructures

O 4.1: Talk

Monday, March 27, 2023, 10:30–10:45, GER 37

High throughput first-principle prediction of interfacial adhesion energies in metal-on-metal contacts — Paolo Restuccia, •Margherita Marsili, and Maria Clelia Righi — Department of Physics and Astronomy, University of Bologna, 40127 Bologna, Italy

Adhesion energy ultimately dictates the mechanical behavior and failure of interfaces. As natural and artificial solid interfaces are ubiquitous, it represents a key quantity in a variety of fields, from geology to nanotechnology. An ab-initio determination of adhesion energies is crucial because the specific atomistic details of the interface primarily determine the strength of adhesion, but, especially for heterogeneous interface is challenging, as computations can be very expensive. We performed the high-throughput DFT determination of the adhesion energy of around a hundred metallic heterostructures, ranging from transition to noble metals [1]. We identified general trends confirming that adhesion energies can be reasonably well inferred from the knowledge of the surface energies of the two interface constituents. Finally, by using a machine learning approach, we obtained a simple analytical expression for predicting the adhesion energy from the intrinsic properties of the two heterostructure constituents alone, which can prove useful for avoiding expensive supercell calculations. These results are part of the SLIDE project funded by the European Research Council under the Horizon 2020 research and innovation program (Grant agreement No. 865633). [1] P. Restuccia et al. High throughput accurate prediction of interfacial adhesion energies in metal-on-metal contacts submitted to npj Computational Materials (2022)