The developments in Transmission and Scanning Transmission Electron Microscopes allowed the production of crystalline images with sub-angstrom resolution. To keep on foot with the massive data produced by the microscopes, automatic techniques and algorithms must be used to analyse the crystalline images.
The objective of this project is to develop an unsupervised or minimally supervised automatic crystal analysis method that can simultaneously segment the crystalline image, determine the unit cell vectors of each grain and detect any existing defects. Variational methods are used to achieve this goal.
This talk will explain the unsupervised extraction method of primitive lattice cells of Mevenkamp and Berkels and the fast automated defect detection method of Elsey and Wirth.
Dr. Amel Shamseldeen Ali (ASP2014 Alumna)