| Abstract Scope |
While the macroscale properties of materials are directly controlled by their atomic and chemical structure, it is imperative to determine and quantitatively access how the microstructural variations arise from synthesis/processing and the macroscale properties they lead to. Electron microscopy imaging and spectroscopy is a powerful technique that provides an insight into the local atomic and electronic structure of materials. Using advanced data analysis and machine learning algorithms, it is possible to extract valuable information about the local atomic and chemical state within the matrix, and near the interfaces and defects, in multi-dimensional datasets. In this talk, we will present our recent work on the quantification of the microstructure, local structural distortions, and valence state, in a wide range of materials, such as oxides and 2D crystals, using advanced data analysis and machine learning algorithms. |