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Bragg Diffraction Imaging : Overcoming Angular Uncertainty

Chen, Huaiyu LU (2025)
Abstract
Probing the internal structure of crystalline materials is vital for understanding and optimizing their functional properties, especially in semiconductors and multiferroics, where nanoscale distortions such as strain and lattice tilt can dramatically affect performance. Among various characterization tools, X-ray diffraction imaging offers a unique combination of deep penetration, nondestructive measurement, and high strain sensitivity.
This thesis focuses on Bragg Cohereht Diffraction Imaging (BCDI), a powerful technique that reconstructs three-dimensional internal displacement fields in crystals from coherent X-ray diffraction patterns. While BCDI offers high-resolution structural information, its practical implementation faces a... (More)
Probing the internal structure of crystalline materials is vital for understanding and optimizing their functional properties, especially in semiconductors and multiferroics, where nanoscale distortions such as strain and lattice tilt can dramatically affect performance. Among various characterization tools, X-ray diffraction imaging offers a unique combination of deep penetration, nondestructive measurement, and high strain sensitivity.
This thesis focuses on Bragg Cohereht Diffraction Imaging (BCDI), a powerful technique that reconstructs three-dimensional internal displacement fields in crystals from coherent X-ray diffraction patterns. While BCDI offers high-resolution structural information, its practical implementation faces a critical challenge: angular instability during data acquisition, which can lead to severe distortions and artifacts in the reconstruction. Addressing this limitation forms the central theme of this work.
A robust angular correction algorithm is developed to mitigate for such distortions, and its effectiveness is demonstrated in experimental studies, including BCDI measurements on heterostructured nanowires. To further relax the stringent sampling requirements of BCDI, a deep learning–based strategy is introduced that enables diffraction volume reconstruction from completely unordered and angularly distorted datasets. Together, these methods aim to enhace the robustness of BCDI and make it more adaptable to complex, dynamic, or extreme experimental conditions.
In addition, scanning X-ray diffraction (nano-XRD) is employed to map local strain and lattice tilt in extended crystalline materials, such as ferroelectric thin films and nanowires. Nano-XRD serves as a practical probe of the internal structure of the extended sample.
Overall, this thesis demonstrates the potential of synchrotron-based X-ray diffraction imgaging tehnique for revealing internal crystalline structures, offering valuable tools for both fundamental research and advanced technological development.
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author
supervisor
opponent
  • Dr. Schülli, Tobias, European Synchrotron Radiation Facility, Grenoble, France
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Coherent Diffraction Imaging, X-ray Diffraction, Nanowires, Strain Mapping, MAX IV
pages
101 pages
publisher
Lund University
defense location
Rydbergsalen
defense date
2025-09-19 09:15:00
ISBN
ISBN 978-91-8104-620-5
ISSN 978-91-8104-621-2
project
eSSENCE@LU 8:2 - Coherent 3D X-ray imaging of nanoparticles with unknown orientation
language
English
LU publication?
yes
id
90237093-0b9b-496c-9069-68f34dac6f34
date added to LUP
2025-08-22 11:44:56
date last changed
2025-08-25 12:07:06
@phdthesis{90237093-0b9b-496c-9069-68f34dac6f34,
  abstract     = {{Probing the internal structure of crystalline materials is vital for understanding and optimizing their functional properties, especially in semiconductors and multiferroics, where nanoscale distortions such as strain and lattice tilt can dramatically affect performance. Among various characterization tools, X-ray diffraction imaging offers a unique combination of deep penetration, nondestructive measurement, and high strain sensitivity.<br/>This thesis focuses on Bragg Cohereht Diffraction Imaging (BCDI), a powerful technique that reconstructs three-dimensional internal displacement fields in crystals from coherent X-ray diffraction patterns. While BCDI offers high-resolution structural information, its practical implementation faces a critical challenge: angular instability during data acquisition, which can lead to severe distortions and artifacts in the reconstruction. Addressing this limitation forms the central theme of this work.<br/>A robust angular correction algorithm is developed to mitigate for such distortions, and its effectiveness is demonstrated in experimental studies, including BCDI measurements on heterostructured nanowires. To further relax the stringent sampling requirements of BCDI, a deep learning–based strategy is introduced that enables diffraction volume reconstruction from completely unordered and angularly distorted datasets. Together, these methods aim to enhace the robustness of  BCDI and make it more adaptable to complex, dynamic, or extreme experimental conditions.<br/>In addition, scanning X-ray diffraction (nano-XRD) is employed to map local strain and lattice tilt in extended crystalline materials, such as ferroelectric thin films and nanowires. Nano-XRD serves as a practical probe of the internal structure of the extended sample.<br/>Overall, this thesis demonstrates the potential of synchrotron-based X-ray diffraction imgaging tehnique for revealing internal crystalline structures, offering valuable tools for both fundamental research and advanced technological development.<br/>}},
  author       = {{Chen, Huaiyu}},
  isbn         = {{ISBN 978-91-8104-620-5}},
  keywords     = {{Coherent Diffraction Imaging; X-ray Diffraction; Nanowires; Strain Mapping; MAX IV}},
  language     = {{eng}},
  publisher    = {{Lund University}},
  school       = {{Lund University}},
  title        = {{Bragg Diffraction Imaging : Overcoming Angular Uncertainty}},
  url          = {{https://lup.lub.lu.se/search/files/225963639/Huaiyu_Chen_-_WEBB.pdf}},
  year         = {{2025}},
}