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About this Symposium
Meeting 2021 TMS Annual Meeting & Exhibition
Symposium Characterization of Materials through High Resolution Imaging
Sponsorship TMS Structural Materials Division
TMS: Advanced Characterization, Testing, and Simulation Committee
Organizer(s) Richard L. Sandberg, Brigham Young University
Ross J. Harder, Argonne National Laboratory
Xianghui Xiao, Brookhaven National Laboratory
Brian Abbey, La Trobe University
Saryu Jindal Fensin, Los Alamos National Laboratory
Ana Diaz, Paul Scherrer Institute
Mathew J. Cherukara, Argonne National Laboratory
Scope This symposium will provide a venue for presentations regarding the use of coherent diffraction imaging techniques (x-ray and electron diffraction imaging, ptychography, holography) and phase contrast imaging techniques for high-resolution characterization in all classes of materials. Additionally, modeling and simulation methods that are relevant to nanoscale imaging techniques will be included.

Background and Rationale:

A high degree of spatial coherence is an attractive property in x-ray and electron beams. Those from modern synchrotrons and electron microscopes have enabled the development of novel imaging methods. In some cases, these imaging methods provide resolution beyond that achieved with optics and can also provide remarkable sensitivity to a variety of contrast mechanisms.

The two methods that will be the focus of this symposium are coherent diffractive imaging (CDI) and phase contrast imaging (PCI) with both x-rays and electrons. Both explicitly take advantage of the coherence properties of the incident beams. CDI has rapidly advanced in the last fifteen years to allow characterization of a broad range of materials, including nanoparticles, strained crystals, biomaterials and cells. PCI has been widely employed in dynamics and engineering studies of materials, geophysics, medicine and biology. Various techniques making use of both x-rays and electrons have been developed that provide unique characterization abilities such as three-dimensional strain mapping and non-destructive three-dimensional quantitative tomographic imaging.

Increasingly, materials modeling at the atomistic and continuum scales is being used in conjunction with these imaging techniques to enhance their capability. Such combined imaging and modeling methods include building experimentally informed models, which are in turn used to make predictions at spatio-temporal scales inaccessible to the imaging technique, and the use of deep learning algorithms trained on synthetic data. These pre-trained deep learning algorithms are being used to improve the quality of acquired x-ray data, reduce experimental measurement times and also reduce compute time required to recover 3D images from raw data.

Finally, as the new 4th generation x-ray light sources (Diffraction Limited Storage Ring or DSLR) come online around the world, increasingly brilliant and coherent x-ray sources will become increasingly important and applicable to those wanting to understand materials behaviors at the mesoscale to nanometer scale. Our 2021 symposium will have a special session dedicated to these new exciting sources and their applications to materials.

Areas of interest include, but are not limited to:

(1) All x-ray based techniques including Bragg CDI, Fresnel CDI, ptychographic CDI, propagation phase contrast imaging, interferometry imaging, and analyzer based phase-contrast imaging

(2) All electron based techniques including ptychography and electron CDI

(3) Computational and simulation efforts with overlap in high resolution imaging.

(4) Big data analytics and machine learning methods to accelerate data abstraction and improve image quality

(4) All structural and functional materials systems needing high resolution imaging

(5) Industrial applications

(6) Development of new techniques and new sources

Abstracts Due 07/20/2020
Proceedings Plan Planned:
PRESENTATIONS APPROVED FOR THIS SYMPOSIUM INCLUDE

Adaptive Machine Learning for 3D Bragg Coherent Diffraction Imaging Reconstructions
Confocal Bragg Ptychography for 3D Mapping of Bulk Specimens
Evaluation of TATB Crystal Morphology for Predicting Sensitivity Using X-ray Computed Tomography
Exploiting Machine Learning Techniques in X-ray Ptychography
High Speed, High Resolution, High Temperature 3D Imaging of Spacecraft Materials during Atmospheric Entry Conditions
ID01 in Light of the ESRF-EBS
Image-based Simulation of Permeability and Image-to-Mesh Conversion of X-ray Tomographic Images of a Nickel Foam
Imaging Materials on the Run: Shedding Light on Fast Structural Processes Using Time-resolved Synchrotron X-ray Tomographic Microscopy
Imaging Phase Transitions of Quantum Materials with Bragg Coherent X-ray Diffraction
Improve Phase Retrieval Performance in Bragg CDI by Simultaneous Reconstruction of Multiple Diffraction Peaks
In Situ and Operando 3D Nano-imaging for Materials Science at the ESRF
Indexing Grains: A Comparison between Three-dimensional Synchrotron X-ray Diffraction and Electron Backscatter Diffraction Techniques
Investigating the Early Life on Earth with Nanoscale X-ray Coherent Imaging
Laboratory and Synchrotron-based X-ray Tomographic Imaging during In Situ Loading of Materials
Magnetic Correlations and Time Fluctuations in Assemblies of Fe3O4 Nanoparticles Probed via X-rays
Megahertz X-ray Microscopy for Imaging High-speed Phenomena in Opaque Materials
Mesoscale Defect Dynamics in the Bulk with Time-resolved Dark-field X-ray Microscopy
Microstructural Characterization and Mechanical Behavior of a Meteorite Using Correlative Microscopy
Multi-peak Phase Retrieval for Coherent X-ray Diffraction Imaging at High Energies
Near-surface Optical Characterisation of Ion Implantation in Titanium Oxide Thin Films
Optimization Based Approach for 3D Alignment in X-ray Nano-tomography
Ptychographic Inversion with Deep Learning Network and Automatic Differentiation
Quantitative Data Analysis of Dynamic Tomography Data with Motion Artifacts
Retrieving the Full 3D Strain Tensor for Nanoscale Materials Science Applications at 34-ID-C
Study of Structure of Beam-sensitive Supported Nanoparticle Catalysts by Low-dose High Resolution Phase Contrast Imaging
The Fourth is Strong in These Ones!
Using Phase Field Simulations to Train Convolutional Neural Networks for Segmentation of Experimental Materials Imaging Datasets
Using the Rotation Vector Base Line Electron Back Scatter Diffraction (RVB-EBSD) Method to Characterize Single Crystal Cast Microstructures
X-ray Based Nanodiffraction to Study Strain in Materials for Nuclear Energy
X-ray Imaging of Three-dimensional Magnetic Systems and Their Dynamics


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