3D Non-Destructive Characterization of Electrical Steels for Quantitative Texture Analysis with Lab-Based X-ray Diffraction Contrast Tomography

2021 ◽  
Author(s):  
Jun Sun ◽  
Ivan Petryshynets ◽  
Li Meng ◽  
Ning Zhang ◽  
Yang Li ◽  
...  
Keyword(s):  
Texture Analysis ◽  
X Ray Diffraction ◽  
Electrical Steels ◽  
X Ray ◽  
Diffraction Contrast ◽  
Non Destructive ◽  
Non Destructive Characterization

Non-destructive characterization of recrystallization kinetics using three-dimensional X-ray diffraction microscopy

2006 ◽  
Vol 55 (1) ◽  
pp. 51-56 ◽  
Author(s):  
E.M. Lauridsen ◽  
S. Schmidt ◽  
S.F. Nielsen ◽  
L. Margulies ◽  
H.F. Poulsen ◽  
...  
Keyword(s):  
Three Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Recrystallization Kinetics ◽  
Non Destructive ◽  
Diffraction Microscopy ◽  
Non Destructive Characterization

scholarly journals Non-destructive characterization of additively manufactured components with x-ray computed tomography for part qualification: A study with laboratory and synchrotron x-rays

2021 ◽  
Vol 173 ◽  
pp. 110894
Author(s):  
Ercan Cakmak ◽  
Philip Bingham ◽  
Ross W. Cunningham ◽  
Anthony D. Rollett ◽  
Xianghui Xiao ◽  
...  
Keyword(s):  
Computed Tomography ◽  
X Rays ◽  
X Ray ◽  
X Ray Computed ◽  
Non Destructive ◽  
Non Destructive Characterization

scholarly journals Energy dispersive X-ray diffraction (EDXRD) for operando materials characterization within batteries

2020 ◽  
Vol 22 (37) ◽  
pp. 20972-20989 ◽  
Author(s):  
Amy C. Marschilok ◽  
Andrea M. Bruck ◽  
Alyson Abraham ◽  
Chavis A. Stackhouse ◽  
Kenneth J. Takeuchi ◽  
...  
Keyword(s):  
Materials Characterization ◽  
Energy Dispersive ◽  
System Level ◽  
X Ray Diffraction ◽  
X Ray ◽  
Non Destructive ◽  
Non Destructive Characterization

This review highlights the efficacy of EDXRD as a non-destructive characterization tool in elucidating system-level phenomena for batteries.

Non-destructive characterization of lithium deposition at the Li/separator and Li/carbon matrix interregion by synchrotron X-ray tomography

Nano Energy ◽  
2019 ◽  
Vol 62 ◽  
pp. 11-19 ◽  
Author(s):  
Kang Dong ◽  
Markus Osenberg ◽  
Fu Sun ◽  
Henning Markötter ◽  
Charl J. Jafta ◽  
...  
Keyword(s):  
Carbon Matrix ◽  
X Ray ◽  
Lithium Deposition ◽  
Non Destructive ◽  
Non Destructive Characterization

Application of X-Ray CT for Non-destructive Characterization of Graphite Fuel-Tube

2016 ◽  
Vol 35 (3) ◽  
Author(s):  
A. K. Agrawal ◽  
P. S. Sarkar ◽  
Y. S. Kashyap ◽  
B. Singh ◽  
A. Sharma ◽  
...  
Keyword(s):  
X Ray ◽  
Non Destructive ◽  
Non Destructive Characterization ◽  
Fuel Tube

scholarly journals A flexible and standalone forward simulation model for laboratory X-ray diffraction contrast tomography

2020 ◽  
Vol 76 (6) ◽  
pp. 652-663 ◽  
Author(s):  
H. Fang ◽  
D. Juul Jensen ◽  
Y. Zhang
Keyword(s):  
Crystal Structure ◽  
Simulation Model ◽  
Forward Simulation ◽  
X Ray Diffraction ◽  
Bulk Materials ◽  
X Ray ◽  
Diffraction Contrast ◽  
Input Structure ◽  
Grain Orientations ◽  
Non Destructive

Laboratory X-ray diffraction contrast tomography (LabDCT) has recently been developed as a powerful technique for non-destructive mapping of grain microstructures in bulk materials. As the grain reconstruction relies on segmentation of diffraction spots, it is essential to understand the physics of the diffraction process and resolve all the spot features in detail. To this aim, a flexible and standalone forward simulation model has been developed to compute the diffraction projections from polycrystalline samples with any crystal structure. The accuracy of the forward simulation model is demonstrated by good agreements in grain orientations, boundary positions and shapes between a virtual input structure and that reconstructed based on the forward simulated diffraction projections of the input structure. Further experimental verification is made by comparisons of diffraction spots between simulations and experiments for a partially recrystallized Al sample, where a satisfactory agreement is found for the spot positions, sizes and intensities. Finally, applications of this model to analyze specific spot features are presented.

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