Explore a cutting-edge lecture on neural network-assisted atomic electron tomography presented by Yongsoo Yang from the Korea Advanced Institute of Science and Technology. Delve into the world of 3D atomic structure measurements with unprecedented precision, using Pt nanoparticles as a model system. Discover how deep learning-based missing data retrieval combined with atomic electron tomography enables reliable surface and interface atomic structure measurements. Examine findings on anisotropic strain distribution, compressive support boundary effects, and full 3D strain tensor mapping. Understand the implications for calculating oxygen reduction reaction activity at the surface. Gain insights into how single-atom level surface characterization can deepen our understanding of nanomaterial properties and pave the way for fine-tuning their performance.
Neural Network-Assisted Atomic Electron Tomography - IPAM at UCLA
Institute for Pure & Applied Mathematics (IPAM) via YouTube
Overview
Syllabus
Yongsoo Yang - Neural network-assisted atomic electron tomography - IPAM at UCLA
Taught by
Institute for Pure & Applied Mathematics (IPAM)