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Meeting TMS Specialty Congress 2024
Symposium 2nd World Congress on Artificial Intelligence in Materials & Manufacturing (AIM 2024)
Presentation Title Persistent Homology for Microstructure Manifold Construction
Author(s) Simon Mason, Jeff Simmons, Megna Shah, Stephen Niezgoda
On-Site Speaker (Planned) Simon Mason
Abstract Scope Quantitative microstructure metrics are an integral component of understanding processing-structure-property relationships. Persistent homology can be used to summarize microstructural features at multiple length scales and fingerprint equivalent microstructures. By developing a method to construct a continuous manifold from microstructure descriptors that can be mapped back to processing conditions, a bi-directional relationship on how processing and microstructure impact each other can be learned. This microstructure manifold can be exploited to better understand regions of processing parameters where local changes have a small or large impact on resulting microstructure, as well as help define safe boundaries for potential processing conditions.
Proceedings Inclusion? Definite: Other

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