Загрузка страницы

Yongsoo Yang - Neural network-assisted atomic electron tomography - IPAM at UCLA

Recorded 26 October 2022. Yongsoo Yang of the Korea Advanced Institute of Science and Technology presents "Neural network-assisted atomic electron tomography" at IPAM's Mathematical Advances for Multi-Dimensional Microscopy Workshop.
Abstract: Functional properties of nanomaterials strongly depend on their surface and interface atomic structures, which often become largely different from their bulk structures, exhibiting surface reconstructions and relaxations. However, most of the surface/interface characterization methods are either limited to 2D measurements or not reaching to true 3D atomic-scale resolution. In this talk, I will demonstrate the measurements of 3D atomic structures at about 15 pm precision using Pt nanoparticles as a model system. Aided by a deep learning-based missing data retrieval combined with atomic electron tomography, the surface/interface atomic structures were reliably measured. From the structures, we found anisotropic strain distribution as well as compressive support boundary effect. A full 3D strain tensor was clearly mapped, which allows direct calculation of the oxygen reduction reaction activity at the surface. The capability of single-atom level surface characterization will not only deepen our understanding of the functional properties of nanomaterials but also open a new door for fine tailoring of their performance.
Learn more online at: http://www.ipam.ucla.edu/programs/workshops/workshop-ii-mathematical-advances-for-multi-dimensional-microscopy/?tab=schedule

Видео Yongsoo Yang - Neural network-assisted atomic electron tomography - IPAM at UCLA канала Institute for Pure & Applied Mathematics (IPAM)
Показать
Комментарии отсутствуют
Введите заголовок:

Введите адрес ссылки:

Введите адрес видео с YouTube:

Зарегистрируйтесь или войдите с
Информация о видео
27 октября 2022 г. 5:30:52
00:47:37
Другие видео канала
Jaafar El-Awady - dislocation in high thermomechanical condition in Additive Manufacturing of AlloysJaafar El-Awady - dislocation in high thermomechanical condition in Additive Manufacturing of AlloysVikram Gavini - Fast, Accurate and Large-scale Ab-initio Calculations for Materials ModelingVikram Gavini - Fast, Accurate and Large-scale Ab-initio Calculations for Materials ModelingBistra Dilkina - Machine Learning for MIP Solving - IPAM at UCLABistra Dilkina - Machine Learning for MIP Solving - IPAM at UCLAAmit Acharya - Slow time-scale behavior of fast microscopic dynamics - IPAM at UCLAAmit Acharya - Slow time-scale behavior of fast microscopic dynamics - IPAM at UCLAEran Rabani - Stochastic Density Functional Theory - IPAM at UCLAEran Rabani - Stochastic Density Functional Theory - IPAM at UCLADeanna Needell - Using Algebraic Factorizations for Interpretable Learning - IPAM at UCLADeanna Needell - Using Algebraic Factorizations for Interpretable Learning - IPAM at UCLAXavier Bresson - Learning to Untangle Genome Assembly Graphs - IPAM at UCLAXavier Bresson - Learning to Untangle Genome Assembly Graphs - IPAM at UCLAJack Gilbert: "Microbiome of the Built Environment"Jack Gilbert: "Microbiome of the Built Environment"John Harrison - Formalization and Automated Reasoning: A Personal and Historical PerspectiveJohn Harrison - Formalization and Automated Reasoning: A Personal and Historical PerspectiveRaymond Clay - Machine Learning in Equation of State and Transport Modeling at Extreme ConditionsRaymond Clay - Machine Learning in Equation of State and Transport Modeling at Extreme ConditionsDavid Ceperley - Quantum Monte Carlo and Machine Learning Simulations of Dense HydrogenDavid Ceperley - Quantum Monte Carlo and Machine Learning Simulations of Dense HydrogenRose Yu - Incorporating Symmetry for Learning Spatiotemporal Dynamics - IPAM at UCLARose Yu - Incorporating Symmetry for Learning Spatiotemporal Dynamics - IPAM at UCLAAlbert Fannjiang - From Tomographic Phase Retrieval to Projection Tomography - IPAM at UCLAAlbert Fannjiang - From Tomographic Phase Retrieval to Projection Tomography - IPAM at UCLAThomas Swinburne - Learning uncertainty-aware models of defect kinetics at scale - IPAM at UCLAThomas Swinburne - Learning uncertainty-aware models of defect kinetics at scale - IPAM at UCLAKevin Kelly - Machine Learning Enhanced Compressive Hyperspectral Imaging - IPAM at UCLAKevin Kelly - Machine Learning Enhanced Compressive Hyperspectral Imaging - IPAM at UCLADemetri Psaltis - Machine Learning for 3D Optical Imaging - IPAM at UCLADemetri Psaltis - Machine Learning for 3D Optical Imaging - IPAM at UCLAPaola Gori-Giorgi - Large-coupling strength expansion in DFT and Hartree-Fock adiabatic connectionsPaola Gori-Giorgi - Large-coupling strength expansion in DFT and Hartree-Fock adiabatic connectionsBohua Zhan - Verifying symbolic computation in the HolPy theorem prover - IPAM at UCLABohua Zhan - Verifying symbolic computation in the HolPy theorem prover - IPAM at UCLAXiantao Li - A stochastic algorithm for self-consistent calculations in DFT - IPAM at UCLAXiantao Li - A stochastic algorithm for self-consistent calculations in DFT - IPAM at UCLAPascal Van Hentenryck - Fusing Machine Learning and Optimization - IPAM at UCLAPascal Van Hentenryck - Fusing Machine Learning and Optimization - IPAM at UCLA
Яндекс.Метрика