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Meeting Materials Science & Technology 2019
Symposium Data Science for Material Property Interpretation
Presentation Title 4D STEM Data Acquisition, Analytics and Functional Material Property Extraction
Author(s) Debangshu Mukherjee, Suhas Somnath, Alex Belianinov, Stephen Jesse, Raymond R. Unocic
On-Site Speaker (Planned) Raymond R. Unocic
Abstract Scope Aberration corrected scanning transmission electron microscopy (STEM) is a powerful characterization tool that allows for the structural and chemical analysis of materials at length scales down to the atomic scale using high spatial resolution imaging, electron diffraction and spectroscopy. Recent advances in high speed electron detectors has opened new opportunities to explore materials functionality using an approach termed 4D STEM. Here, a sub--sized electron probe is rastered through the material of interest and the scattered electrons, containing information rich, 2D diffraction patterns acquired pixel-by-pixel at every electron probe position, are collected by the detector. The 4D STEM data sets (e.g. probe position (x,y) and diffraction pattern (x’,y’), are inherently large which necessitates a big-data analytics approach to process then analyze the data to obtain meaningful information. Here we will discuss our data analytics approach with relevant examples for strain mapping of catalyst nanoparticles and electron ptychography of 2D materials.
Proceedings Inclusion? Definite: At-meeting proceedings


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