Speaker: Petra Reinke, University of Virginia
Abstract: This seminar will discuss a wide range of 2D materials and their modulation at the nanoscale. The presentation is subdivided into four sections focusing on intercalation, synthesis, defects, tip induced etching – all studied with STM - and the use of machine learning to advance TMD growth (or why metadata matter). The intercalation of fullerenes between a graphene layer and Cu substrate is used to imprint a strain superlattice. The intercalation is feasible in a relatively narrow temperature range, and amorphous and crystalline superlattices can be formed. The deformation energy of the graphene and its interaction with Cu define the superlattice. The superlattice modulates the electronic structure and we hypothesize that it can lead to a differential reactivity across the surface. The substrate-2D material interactions are also critical in the synthesis and stabilization of silicene layers, where a quasi-free standing layer is coveted. I will discuss whether silicene layers and ribbons formed on hexagonal Mo-disilicide crystallites conform to this ideal. The role of silicene-substrate interaction and its impact on layer buckling are particularly important in this context. Lastly, I will introduce a study on the thermal stability of WSe2 . The defects on the few layer TMD are mapped with STS and classified with respect to their electronic properties (p, n, neutral). The conclusion of the seminar touches on the question on how to use literature data to advance materials synthesis for MoS2. Or more specifically, the challenges in establishing correlations using ML methods from published, metadata-poor information.