Snapshot full-volume coded aperture x-ray diffraction tomography

2016 ◽  
Author(s):  
Joel A. Greenberg ◽  
David J. Brady
Keyword(s):  
Coded Aperture ◽  
Diffraction Tomography ◽  
X Ray Diffraction ◽  
X Ray ◽  
Full Volume

Development of a novel apparatus for experiments in soft X-ray diffraction imaging and diffraction tomography

2003 ◽  
Vol 104 ◽  
pp. 27-30 ◽  
Author(s):  
T. Beetz ◽  
C. Jacobsen ◽  
C.-C. Kao ◽  
J. Kirz ◽  
O. Mentes ◽  
...  
Keyword(s):  
Diffraction Tomography ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Imaging

scholarly journals Mapping the coke formation within a zeolite catalyst extrudate in space and time by operando computed X-ray diffraction tomography

2021 ◽  
Author(s):  
David S. Wragg ◽  
Georgios N. Kalantzopoulos ◽  
Dimitrios K. Pappas ◽  
Irene Pinilla-Herrero ◽  
Daniel Rojo-Gama ◽  
...  
Keyword(s):  
Zeolite Catalyst ◽  
Coke Formation ◽  
Diffraction Tomography ◽  
X Ray Diffraction ◽  
X Ray ◽  
Space And Time

scholarly journals Coded cone-beam x-ray diffraction tomography with a low-brilliance tabletop source

Optica ◽  
2018 ◽  
Vol 5 (6) ◽  
pp. 733 ◽  
Author(s):  
Zheyuan Zhu ◽  
Ryan A. Ellis ◽  
Shuo Pang
Keyword(s):  
Cone Beam ◽  
Diffraction Tomography ◽  
X Ray Diffraction ◽  
X Ray

scholarly journals Synchrotron X-ray diffraction tomography technique using diamond anvil cell

2011 ◽  
Vol 67 (a1) ◽  
pp. C113-C113
Author(s):  
H. Liu ◽  
L. Wang ◽  
Z. Yu ◽  
L. Kong ◽  
J. Zhao ◽  
...  
Keyword(s):  
Diamond Anvil Cell ◽  
Diffraction Tomography ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diamond Anvil

scholarly journals PolyProc: A Modular Processing Pipeline for X-ray Diffraction Tomography

2019 ◽  
Vol 8 (3) ◽  
pp. 388-399 ◽  
Author(s):  
Jiwoong Kang ◽  
Ning Lu ◽  
Issac Loo ◽  
Nancy Senabulya ◽  
Ashwin J. Shahani
Keyword(s):  
Three Dimensional ◽  
Valuable Insight ◽  
Diffraction Tomography ◽  
Computationally Efficient ◽  
X Ray Diffraction ◽  
Orientation Data ◽  
Bulk Specimen ◽  
X Ray ◽  
Data Alignment ◽  
And Performance

Abstract Direct imaging of three-dimensional microstructure via X-ray diffraction-based techniques gives valuable insight into the crystallographic features that influence materials properties and performance. For instance, X-ray diffraction tomography provides information on grain orientation, position, size, and shape in a bulk specimen. As such techniques become more accessible to researchers, demands are placed on processing the datasets that are inherently “noisy,” multi-dimensional, and multimodal. To fulfill this need, we have developed a one-of-a-kind function package, PolyProc, that is compatible with a range of data shapes, from planar sections to time-evolving and three-dimensional orientation data. Our package comprises functions to import, filter, analyze, and visualize the reconstructed grain maps. To accelerate the computations in our pipeline, we harness computationally efficient approaches: for instance, data alignment is done via genetic optimization; grain tracking through the Hungarian method; and feature-to-feature correlation through k-nearest neighbors algorithm. As a proof-of-concept, we test our approach in characterizing the grain texture, topology, and evolution in a polycrystalline Al–Cu alloy undergoing coarsening.

scholarly journals Correction to: PolyProc: A Modular Processing Pipeline for X-ray Diffraction Tomography

2020 ◽  
Vol 9 (1) ◽  
pp. 151-151
Author(s):  
Jiwoong Kang ◽  
Ning Lu ◽  
Issac Loo ◽  
Nancy Senabulya ◽  
Ashwin J. Shahani
Keyword(s):  
Diffraction Tomography ◽  
X Ray Diffraction ◽  
X Ray ◽  
Processing Pipeline

High Resolution Synchrotron X-Ray Diffraction Tomography Of Large-Grained Samples

1996 ◽  
Vol 437 ◽  
Author(s):  
D.P. Piotrowski ◽  
S.R. Stock ◽  
A. Guvenilir ◽  
J.D. Haase ◽  
Z.U. Rek
Keyword(s):  
Spatial Distribution ◽  
High Resolution ◽  
Three Dimensional ◽  
Polycrystalline Materials ◽  
Diffraction Tomography ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
Image Storage ◽  
X Ray ◽  
Dimensional Distribution

AbstractIn order to understand the macroscopic response of polycrystalline structural materials to loading, it is frequently essential to know the spatial distribution of strain as well as the variation of micro-texture on the scale of 100 μm. The methods must be nondestructive, however, if the three-dimensional evolution of strain is to be studied. This paper describes an approach to high resolution synchrotron x-ray diffraction tomography of polycrystalline materials. Results from model samples of randomly-packed, millimeter-sized pieces of Si wafers and of similarly sized single-crystal Al blocks have been obtained which indicate that polychromatic beams collimated to 30 μm diameter can be used to determine the depth of diffracting volume elements within ± 70 μm. The variation in the two-dimensional distribution of diffracted intensity with changing sample to detector separation is recorded on image storage plates and used to infer the depth of diffracting volume elements.

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