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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Algorithm Development in Materials Science and Engineering
Presentation Title Persistent Homology for Topological Quantification of Microstructure
Author(s) Simon Mason, Dennis Dimiduk, Steve Niezgoda
On-Site Speaker (Planned) Simon Mason
Abstract Scope Given the central role of microstructure in property and processing relationships in materials science, having quantitative metrics for the description and characterization of microstructure is essential for the continued development of microstructure-sensitive design. Traditional statistical microstructure descriptors (SMDs), such as n-point statistics, allow for the analysis of spatial relationships of features, capture key short range geometrical features but are largely insensitive to long range connectivity . Topological descriptors built on persistent homology capture this connectivity by tracking the appearance and disappearance of connected components and holes in multiple dimensions as persistence diagrams, and related reduced order metrics such as persistence landscapes. Persistence landscapes in particular are well suited for formulating statistical tests for comparing microstructure. These topological measures can also serve as quality metrics for microstructure generation, either through traditional methods such as using DREAM.3D or to assess the development of novel ML methods.
Proceedings Inclusion? Planned:
Keywords Computational Materials Science & Engineering, ICME,

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