Cluster-mining: an approach for determining core structures of metallic nanoparticles from atomic pair distribution function data
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99 GENERAL AND MISCELLANEOUS↗
Engineering topics
Juhas, Pavol
Publications and source records attributed to Juhas, Pavol.
Complex imaging of phase domains by deep neural networks
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Wu, Longlong↗
Provenance infrastructure for multimodal x-ray experiments and reproducible analysis
Exploring relationships between material structures and desired properties for material discovery and synthesis requires mining machine-readable databases and linking experimental data with sufficiently rich annotations. There are vast gaps both in these data sources and in the connections between them. We present a provenance-based data management and analysis framework that enables capturing, persisting, and reanalyzing experimental data from the BNL National Synchrotron Light Source II (NSLS-II). Our system leverages NSLS-II Bluesky for experimental data acquisition, captures analysis parameters, and enriches the search space with results from the scientific literature. We describe in detail the challenges and benefits of data-driven approaches when comparing computational and experimental data, such as the multiple possible scenarios of interest in often ill-posed inverse problems and missing data. Our infrastructure utilizes the NSLS-II event model and includes discovery mechanisms across multiple beamlines. A text and data mining module using natural language processing classification techniques extracts relevant information from the literature that is added to data sources. We describe a provenance acquisition and analysis rerun workflow based on a directed acyclic graph that keeps track of process and data provenance and allows to replay analysis.
97 MATHEMATICS AND COMPUTING↗