In this poster, we present our research goals of a recently BiGmax funded project towards learning dynamics of scanning transmission electron microscopy (STEM) by incorporating physical consistency with phase-field models. The primary idea of this project is to develop machine learning (ML)-based modeling of an interpretable coarse-grained dynamic model utilizing in situ STEM video sequences...
To correlate mechanical properties of Al alloys with chemical segregation in Atom Probe Tomography (APT), we have developed two approaches. In the first, we collect composition statistics from APT datasets for 2x2x2 nm voxels. These voxel compositions are then clustered in compositional space using Gaussian mixture models to automatically identify key phases and their corresponding statistical...
Mapping of the electronic band structures of materials using momentum microscopy requires processing single-electron events of a few to hundreds of gigabytes. We construct a flexible computational workflow that allows user interaction with billion-count single-electron events in these band mapping experiments. We demonstrate its compatibility with large facility and tabletop experimental...
