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Meeting 2023 TMS Annual Meeting & Exhibition
Symposium Characterization of Materials through High Resolution Coherent Imaging
Sponsorship TMS Extraction and Processing Division
TMS Structural Materials Division
TMS: Advanced Characterization, Testing, and Simulation Committee
TMS: Materials Characterization 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 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 twenty 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 such as the ESRF in France or APS in Argonne National Laboratory, these 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 2023 symposium will have a special session dedicated to imaging
experiments at these exciting new 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
(5). All structural and functional materials systems needing high resolution imaging
(6). Industrial applications
(7.) Development of new techniques and new sources

Abstracts Due 07/01/2022
Proceedings Plan Undecided
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