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Explore cutting-edge strategies for quantitative imaging and reconstruction from high-speed and low-dose data in this comprehensive lecture by Angus Kirkland from the University of Oxford. Delve into recent developments in Scanning Transmission and Transmission Electron Microscopy for quantitative structural studies of materials under challenging conditions. Discover how high-speed direct electron detectors and artificial intelligence/machine learning techniques are revolutionizing the mapping of defect and adatom migrations in graphene. Examine the application of these approaches to probe local kinetics of defect transitions and understand industrial catalysts. Learn about overcoming challenges in processing extremely large datasets using deep learning neural networks for atomic model abstraction. Investigate the use of fast detectors for optimized phase retrieval and explore the challenges of applying electron ptychography under low-dose conditions. Gain insights into dose-efficient strategies for studying biological molecules and larger structures.
