Fast Grain Mapping with Sub-Nanometer Resolution Using 4D-STEM with Grain Classification by Principal Component Analysis and Non-Negative Matrix Factorization

High-throughput grain mapping with sub-nanometer spatial resolution is demonstrated using scanning nanobeam electron diffraction (also known as 4D transmission microscopy, or 4D-STEM) combined high-speed direct detection. An probe size down to 0.5 nm in diameter implemented and the sample investigated a gold-palladium nanoparticle catalyst. Computational analysis of 4D-STEM data sets performed disk registration algorithm identify peaks followed by feature learning map individual grains. Two unsupervised techniques are compared: Principal component (PCA) non-negative matrix factorization (NNMF). The characteristics PCA versus NNMF output compared potential approach for statistical orientations at high discussed.