Discipline: Mathematics and Statistics
Subcategory: Materials Science
Room: Park Tower 8211
Vincent Davis - North Carolina Central University
Co-Author(s): Sihan (Shirley) Wang, NC State University, Raleigh, NC; Dr. Srikanth Patala, NC State University, Raleigh, NC; Dr. Elizabeth Dickey, NC State University, Raleigh, NC
Electron backscatter diffraction (EBSD) is a technique that describes the orientation of crystals in a sample. A series of deep convolutional neural networks was built to determine the orientation of a polycrystalline sample based on its electron diffraction patterns. By establishing a fixed coordinate system, a mathematical model will take jpg files of a series of rotations as training data at a rate of approximately 250 seconds on each epoch. The networks determine the orientation of a sample image at substantially higher orders than traditional physics-based forward models. Statistical techniques are applied within the model to attain a loss in accuracy of only 5-8 degrees for rotations between 0 and 360 degrees. This simple and robust python software tool can be utilized in further offline analysis to index electron diffraction patterns much more efficiently while maintaining an average level of accuracy greater than or equal to 80%.
Funder Acknowledgement(s): NSF DGE: 1633587
Faculty Advisor: Kimberly Weems, email@example.com
Role: Research into the development and implementation of several types of Neural Networks. Additionally a Hierarchical Neural Network was successfully modeled and tested.