Search for: All records

A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.

 

Robust atomic-to-meso-scale chirality is now observed in the one-dimensional form of tellurium. This enables a large and counter-intuitive circular-polarization dependent second harmonic generation response above 0.2 which is not present in two-dimensional tellurium. Orientation variations in 1D tellurium nanowires obtained by four-dimensional scanning transmission electron microscopy (4D-STEM) and their correlation with unconventional non-linear optical properties by second harmonic generation circular dichroism (SHG-CD) uncovers an unexpected circular-polarization dependent SHG response from 1D nanowire bundles – an order-of-magnitude higher than in single-crystal two-dimensional tellurium structures – suggesting the atomic- and meso-scale crystalline structure of the 1D material possesses an inherent chirality not present in its 2D form; and which is strong enough to manifest even in the aggregate non-linear optical (NLO) properties of aggregates.