Abstract: The interplay between strain and composition is at the basis of heterostructure design to engineer new properties. The influence of the strain distribution on the incorporation of indium during the formation of multiple InGaN/GaN quantum dots (QDs) in nanowire (NW) heterostructures has been investigated, using the combined techniques of geometric phase analysis of atomic-resolution images and quantitative elemental mapping from core-loss electron energy-loss spectroscopy within scanning transmission electron microscopy. The variation in In-content between successive QDs within individual NWs shows a dependence on the magnitude of compressive strain along the growth direction within the underlying GaN barrier layer, which affects the incorporation of In-atoms to minimize the local effective strain energy. Observations suggest that the interfacial misfit between InGaN/GaN within the embedded QDs is mitigated by strain partitioning into both materials, and results in normal stresses inflicted by the presence of the surrounding GaN shell. These experimental measurements are linked to the local piezoelectric polarization fields for individual QDs, and are discussed in terms of the photoluminescence from an ensemble of NWs.

Abstract: Following an extensive investigation of various monolayer transition metal dichalcogenides (MX2), research interest has expanded to include multilayer systems. In bilayer MX2, the stacking order strongly impacts the local band structure as it dictates the local confinement and symmetry. Determination of stacking order in multilayer MX(2)domains usually relies on prior knowledge of in-plane orientations of constituent layers. This is only feasible in case of growth resulting in well-defined triangular domains and not useful in-case of closed layers with hexagonal or irregularly shaped islands. Stacking order can be discerned in the reciprocal space by measuring changes in diffraction peak intensities. Advances in detector technology allow fast acquisition of high-quality four-dimensional datasets which can later be processed to extract useful information such as thickness, orientation, twist and strain. Here, we use 4D scanning transmission electron microscopy combined with multislice diffraction simulations to unravel stacking order in epitaxially grown bilayer MoS2. Machine learning based data segmentation is employed to obtain useful statistics on grain orientation of monolayer and stacking in bilayer MoS2.