Regensburg 2025 – scientific programme
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MM: Fachverband Metall- und Materialphysik
MM 27: Transport in Materials: Diffusion, Charge or Heat Conduction
MM 27.5: Talk
Thursday, March 20, 2025, 11:15–11:30, H22
Influence of Defects and Layer Twisting on Phonon Dynamics in Bilayer Graphene and MoS2 Using Machine Learned-Force Field Calculations — •Sabuhi Badalov1,2 and Harald Oberhofer1,2 — 1Department of Physics, University of Bayreuth — 2Bavarian Center for Battery Technology, Bayreuth, Germany
In crystalline materials, thermal, mechanical and even electronic properties are often described in terms phonon spectra and dynamics. These, can, to a large degree be influenced by even minute structural changes, such as through defects or by altering the relative alignment of a material’s layers. By means of a state-of-the-art machine learning-augmented force field approach, we carry out extensive phonon calculations to understand how the defect density and layer configurations influence the phonon spectra in bilayer graphene and MoS2. Our results highlight an interplay of phononic phenomena with the materials’ Moiré patterns with major consequences on the transport properties of these materials. Moreover, we explore the possibility of phonon-mediated superconductivity through the electron-phonon coupling in topologically nontrivial phonon states. While this is still ongoing research, our results so far not only further the understanding of phonon dynamics in 2D materials, but also offer a solid foundation for future investigations into harnessing topological phonons for advanced electronic and thermal control technologies.
Keywords: 2D materials; DFT; Machine Learning-Force Field