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Meeting 2024 TMS Annual Meeting & Exhibition
Symposium AI/Data Informatics: Computational Model Development, Verification, Validation, and Uncertainty Quantification
Presentation Title Finding “Trigger Sites” of Reactions Among Heterogeneous Materials From X-ray Microscopic Big Data Using Persistent Homology
Author(s) Masao Kimura, Ippei Obayashi, Daiki Kido, Yasuhiro Niwa, Xichan Gao, Kazuto Akagi
On-Site Speaker (Planned) Masao Kimura
Abstract Scope Material properties are often determined by specific features in heterogeneity (or ‘trigger sites’) of phases, chemical states, etc. We have investigated trigger sites in structural materials, batteries, etc. using X-ray microscopy (XRM) at multiscale. However, finding trigger sites by humans or computers has been a challenging task because the data is not only big but also multi-dimensional. Here we developed a new approach for determining trigger sites in terms of the shapes of heterogeneity in XRM data using persistent homology (PH) analysis. We will present two typical results: (1) finding the trigger sites of heterogeneous reduction of iron ore sinters: the complex of Ca-Fe-O oxides and pores, and (2) finding the crack initiation sites at nanoscale in carbon-fiber reinforced plastics (CFRP) under load. We could non-empirically identify the trigger sites from the big data obtained by XRM. This approach can be applied to find trigger sites in various materials.
Proceedings Inclusion? Planned:
Keywords Characterization, Iron and Steel, Composites

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