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The Dynamic PicoProbe at Argonne National Laboratory is undergoing upgradesthat will enable it to produce up to 100s of GB of data per day. While thisdata is highly important for both fundamental science and industrialapplications, there is currently limited on-site infrastructure to handle thesehigh-volume data streams. We address this problem by providing a softwarearchitecture capable of supporting large-scale data transfers to theneighboring supercomputers at the Argonne Leadership Computing Facility. Toprepare for future scientific workflows, we implement two instructive use casesfor hyperspectral and spatiotemporal datasets, which include: (i) off-site datatransfer, (ii) machine learning/artificial intelligence and traditional dataanalysis approaches, and (iii) automatic metadata extraction and cataloging ofexperimental results. This infrastructure supports expected workloads and alsoprovides domain scientists the ability to reinterrogate data from pastexperiments to yield additional scientific value and derive new insights.

Linking the Dynamic PicoProbe Analytical Electron-Optical Beam Line / Microscope to Supercomputers