About this Abstract |
Meeting |
MS&T24: Materials Science & Technology
|
Symposium
|
Manufacturing and Processing of Advanced Ceramic Materials
|
Presentation Title |
Microstructure Classification and the Microstructure State Space |
Author(s) |
Dylan Miley, Ethan Suwandi, Benjamin Schweinhart, Jeremy K. Mason |
On-Site Speaker (Planned) |
Jeremy K. Mason |
Abstract Scope |
Material microstructures are traditionally compared using incomplete statistical measures, e.g., two visually distinct microstructures can have identical grain size distributions and phase fractions. A general approach to quantitatively compare microstructures would support the realization of integrated computational materials engineering (ICME) by enabling the correlation of processing routes with microstructures and of microstructures with material properties. This work proposes a (pseudo) metric on the space of grain boundary networks such that two microstructures that are close with respect to the metric are statistically similar in every respect of grain geometry below a user-specified length scale. Given a pair of micrographs, the metric is approximated by sampling windows from the micrographs, defining a distance between pairs of windows, and finding a window matching that minimizes the sum of pairwise window distances. The approach is used to show the viability of a general polycrystalline material microstructure database with a lookup capability. |