Maria Chan1

1, Argonne National Laboratory, Argonne, Illinois, United States

Electronic, mechanical, transport, and electrochemical properties of composite materials are significantly influenced by the presence and characteristics of interfaces such as grain boundaries and interfaces between electrodes and electrolytes. Atomistic structures at interfaces can be characterized by electron and x-ray characterization techniques, and at the same time atomistic and first principles modeling has been used to obtain interfacial structures as well as properties. In this talk, we will discuss efforts to combine atomistic modeling (including using first principles density functional theory and interatomic potentials) and electron and x-ray measurements, under an automated framework making use of machine learning and computer vision, to produce atomistic structures at interfaces. Relevant electronic and transport properties of the interfaces will also be discussed.