About this Abstract |
Meeting |
2024 TMS Annual Meeting & Exhibition
|
Symposium
|
Algorithm Development in Materials Science and Engineering
|
Presentation Title |
Microstructural Interrogation Using Information Theory and Correlative Statistics |
Author(s) |
Jeffrey M. Rickman |
On-Site Speaker (Planned) |
Jeffrey M. Rickman |
Abstract Scope |
The spatio-temporal evolution of microstructural features in metals and ceramics has been the subject of intense investigation over many years as such features often influence material properties that dictate structural and functional applications. In this talk, I examine the kinetics of evolving synthetic and experimental microstructures as quantified by their embodied information and from the perspective of a marked point process focused on grain triple junctions. More specifically, microstructural evolution is quantified using two, interrelated approaches, namely: 1.) tracking the information content of coarsening microstructures via selected metrics and measures of shared information and interaction strength, and 2.) determining the interaction of triple junctions via a correlation function analysis. These approaches permit one to characterize dynamically evolving microstructures and to identify correlation times associated with different coarsening scenarios. As the information content of a system is a proxy for the entropy, a thermodynamic description of grain growth is also outlined. |
Proceedings Inclusion? |
Planned: |
Keywords |
Computational Materials Science & Engineering, Modeling and Simulation, |