Deep Neural Networks in Electron Microscopy of Quantum Materials: From Learning Physics to Atomic Manipulation

Atomically-resolved imaging of materials has become the mainstay of modern materials science, as enabled by advent of aberration corrected scanning transmission electron microscopy (STEM). However, the wealth of quantitative information contained in the fine details of atomic structure or spectra remains largely unexplored. In this talk, I will present the new opportunities enabled by physics-informed big data and machine learning technologies to extract physical information from static and dynamic STEM images. The deep learning models trained on theoretically simulated images or labeled library data demonstrate extremely high efficiency in extracting atomic coordinates and trajectories, converting massive volumes of statistical and dynamic data into structural descriptors. I further present a method to take advantage of atomic-scale observations of chemical and structural fluctuations and use them to build a generative model (including near-neighbor interactions) that can be used to predict the phase diagram of the system in a finite temperature and composition space. Similar approach is applied to probe the kinetics of solid-state reactions on a single defect level and defect formation in solids via atomic-scale observations. Finally, synergy of deep learning image analytics and real-time feedback further allows harnessing beam-induced atomic and bond dynamics to enable direct atom-by-atom fabrication. Examples of direct atomic motion over mesoscopic distances, engineered doping at selected lattice site, and assembly of multiatomic structures will be demonstrated. These advances position STEM towards transition from purely imaging tool for atomic-scale laboratory of electronic, phonon, and quantum phenomena in atomically-engineered structures.
This research was sponsored by the Division of Basic Energy Sciences, BES, DOE, and was conducted at the Center for Nanophase Materials Sciences, sponsored at Oak Ridge National Laboratory by the Scientific User Facilities Division.
Bio: Sergei V. Kalinin is the director of the ORNL Institute for Functional Imaging of Materials and distinguished research staff member at the Center for Nanophase Materials Sciences (CNMS) at Oak Ridge National Laboratory, as well as a theme leader for Electronic and Ionic Functionality on the Nanoscale (at ORNL since 2002). He also holds a Joint Associate Professor position at the Department of Materials Science and Engineering at the University of Tennessee-Knoxville, and an Adjunct Faculty position at Pennsylvania State University. His research interests include application of big data, deep data, and smart data approaches in atomically resolved and mesoscopic imaging to guide the development of advanced materials for energy and information technologies, as well as coupling between electromechanical, electrical, and transport phenomena on the nanoscale. He received his Ph.D. from the University of Pennsylvania in 2002, followed by a Wigner fellowship at ORNL (2002-2004). He is a recipient of the Blavatnik National Awards for Young Scientists (2018); RMS medal for Scanning Probe Microscopy (2015); Presidential Early Career Award for Scientists and Engineers (PECASE) (2009); IEEE-UFFC Ferroelectrics Young Investigator Award (2010); Burton medal of Microscopy Society of America (2010); ISIF Young Investigator Award (2009); American Vacuum Society Peter Mark Memorial Award (2008); R&D100 Awards (2008 and 2010); Ross Coffin Award (2003); Robert L. Coble Award of American Ceramics Society (2009); and a number of other distinctions. He has published more than 500 peer-reviewed journal papers, edited 3 books, and holds more than 10 patents. He has organized numerous symposia (including symposia on Scanning Probe Microscopy on Materials Research Society Fall meeting in 2004, 2007, and 2009) and workshops (including International workshop series on PFM and Nanoferroelectrics), and acted as consultant for companies such as Intel and several Scanning Probe Microscopy manufacturers. He is also a member of editorial boards for several international journals, including Nanotechnology, Journal of Applied Physics/Applied Physics Letters, and recently established Nature Partner Journal Computational Materials.