scholarly journals Dark-field phase retrieval under the constraint of the Friedel symmetry in coherent X-ray diffraction imaging

2014 ◽  
Vol 22 (23) ◽  
pp. 27892 ◽  
Author(s):  
Amane Kobayashi ◽  
Yuki Sekiguchi ◽  
Yuki Takayama ◽  
Tomotaka Oroguchi ◽  
Masayoshi Nakasako
Keyword(s):  
Phase Retrieval ◽  
Dark Field ◽  
X Ray Diffraction ◽  
Field Phase ◽  
X Ray ◽  
Diffraction Imaging

scholarly journals The influence of strain on image reconstruction in Bragg coherent X-ray diffraction imaging and ptychography

2021 ◽  
Vol 28 (4) ◽  
Author(s):  
Chan Kim ◽  
Markus Scholz ◽  
Anders Madsen
Keyword(s):  
Phase Retrieval ◽  
Superlattice Reflection ◽  
Antiphase Domain ◽  
Phase Changes ◽  
X Ray Diffraction ◽  
X Ray ◽  
Domain Boundaries ◽  
Diffraction Imaging ◽  
Highly Strained ◽  
The Impact

A quantitative analysis of the effect of strain on phase retrieval in Bragg coherent X-ray diffraction imaging is reported. It is shown in reconstruction simulations that the phase maps of objects with strong step-like phase changes are more precisely retrieved than the corresponding modulus values. The simulations suggest that the reconstruction precision for both phase and modulus can be improved by employing a modulus homogenization (MH) constraint. This approach was tested on experimental data from a highly strained Fe–Al crystal which also features antiphase domain boundaries yielding characteristic π phase shifts of the (001) superlattice reflection. The impact of MH is significant and this study outlines a successful method towards imaging of strong phase objects using the next generation of coherent X-ray sources, including X-ray free-electron lasers.

scholarly journals Three-dimensional coherent X-ray diffraction imaging via deep convolutional neural networks

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Longlong Wu ◽  
Shinjae Yoo ◽  
Ana F. Suzana ◽  
Tadesse A. Assefa ◽  
Jiecheng Diao ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Phase Retrieval ◽  
Three Dimensional ◽  
Current Phase ◽  
X Ray Diffraction ◽  
Deep Convolutional Neural Networks ◽  
X Ray ◽  
Model Combining ◽  
Diffraction Imaging ◽  
Improved Performance

AbstractAs a critical component of coherent X-ray diffraction imaging (CDI), phase retrieval has been extensively applied in X-ray structural science to recover the 3D morphological information inside measured particles. Despite meeting all the oversampling requirements of Sayre and Shannon, current phase retrieval approaches still have trouble achieving a unique inversion of experimental data in the presence of noise. Here, we propose to overcome this limitation by incorporating a 3D Machine Learning (ML) model combining (optional) supervised learning with transfer learning. The trained ML model can rapidly provide an immediate result with high accuracy which could benefit real-time experiments, and the predicted result can be further refined with transfer learning. More significantly, the proposed ML model can be used without any prior training to learn the missing phases of an image based on minimization of an appropriate ‘loss function’ alone. We demonstrate significantly improved performance with experimental Bragg CDI data over traditional iterative phase retrieval algorithms.

scholarly journals Phase Retrieval by Combined Bragg and Fresnel X-Ray Diffraction Imaging

1998 ◽  
Vol 81 (16) ◽  
pp. 3435-3438 ◽  
Author(s):  
P. Rejmánková-Pernot ◽  
P. Cloetens ◽  
J. Baruchel ◽  
J.-P. Guigay ◽  
P. Moretti
Keyword(s):  
Phase Retrieval ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Imaging

scholarly journals Bonsu: the interactive phase retrieval suite

2012 ◽  
Vol 45 (4) ◽  
pp. 840-843 ◽  
Author(s):  
Marcus C. Newton ◽  
Yoshinori Nishino ◽  
Ian K. Robinson
Keyword(s):  
Phase Retrieval ◽  
Nondestructive Method ◽  
Three Dimensions ◽  
Material Structure ◽  
X Ray Diffraction ◽  
Data Manipulation ◽  
X Ray ◽  
Python Language ◽  
Real Time Visualization ◽  
Diffraction Imaging

Coherent X-ray diffraction imaging has received considerable attention as a nondestructive method for probing material structure at the nanoscale. However, tools for reconstructing and analysing data in both two and three dimensions have lagged somewhat behind.Bonsu, the interactive phase retrieval suite, is the first software package that allows real-time visualization of the reconstruction of phase information in both two and three dimensions. It comes complete with an inventory of algorithms and routines for data manipulation and reconstruction.Bonsuis open source, is designed around the Python language (with C++ bindings) and is largely platform independent.Bonsuis made available under version three of the GNU General Public License and can be found at https://code.google.com/p/bonsu/.

scholarly journals Towards a quantitative determination of strain in Bragg Coherent X-ray Diffraction Imaging: artefacts and sign convention in reconstructions

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jérôme Carnis ◽  
Lu Gao ◽  
Stéphane Labat ◽  
Young Yong Kim ◽  
Jan P. Hofmann ◽  
...  
Keyword(s):  
Displacement Field ◽  
Phase Retrieval ◽  
Dynamic Range ◽  
Surface Strain ◽  
Three Dimensions ◽  
X Ray Diffraction ◽  
X Ray ◽  
Retrieval Algorithms ◽  
Diffraction Imaging

AbstractBragg coherent X-ray diffraction imaging (BCDI) has emerged as a powerful technique to image the local displacement field and strain in nanocrystals, in three dimensions with nanometric spatial resolution. However, BCDI relies on both dataset collection and phase retrieval algorithms that can induce artefacts in the reconstruction. Phase retrieval algorithms are based on the fast Fourier transform (FFT). We demonstrate how to calculate the displacement field inside a nanocrystal from its reconstructed phase depending on the mathematical convention used for the FFT. We use numerical simulations to quantify the influence of experimentally unavoidable detector deficiencies such as blind areas or limited dynamic range as well as post-processing filtering on the reconstruction. We also propose a criterion for the isosurface determination of the object, based on the histogram of the reconstructed modulus. Finally, we study the capability of the phasing algorithm to quantitatively retrieve the surface strain (i.e., the strain of the surface voxels). This work emphasizes many aspects that have been neglected so far in BCDI, which need to be understood for a quantitative analysis of displacement and strain based on this technique. It concludes with the optimization of experimental parameters to improve throughput and to establish BCDI as a reliable 3D nano-imaging technique.

Coherent X-ray diffraction imaging meets ptychography to study core-shell-shell nanowires

MRS Advances ◽  
2018 ◽  
Vol 3 (39) ◽  
pp. 2317-2322 ◽  
Author(s):  
A. Davtyan ◽  
V. Favre-Nicolin ◽  
R. B. Lewis ◽  
H. Küpers ◽  
L. Geelhaar ◽  
...  
Keyword(s):  
Phase Retrieval ◽  
Bragg Reflection ◽  
Rotational Symmetry ◽  
Core Shell ◽  
X Ray Diffraction ◽  
Bottom Part ◽  
X Ray ◽  
Structural Homogeneity ◽  
Diffraction Imaging ◽  
Diffraction Patterns

AbstractWe report on the results of coherent X-ray diffraction imaging (CXDI) and ptychography measurements of two individual core-shell-shell GaAs/(In,Ga)As/GaAs nanowires (NWs) grown by molecular beam epitaxy (MBE) on patterned Si(111) substrate. CXDI at the axial GaAs 111 Bragg reflection was applied at different positions along the NW axis in order to characterize the NWs in terms of structural homogeneity along the radial directions. At each positon 3D reciprocal space maps have been recoded and inverted using phase retrieval algorithms. The CXDI were complemented by 2D ptychography measurements at GaAs 111 Bragg reflection probing the same NWs with respect to their structural homogeneity. Both methods provide structural homogeneity for NW1 and NW2 except at the bottom part of the NWs. In case of NW2 CXDI and ptychography show changes in the structure of the top part of the NW indicated by 60° rotation of the indicated three-fold rotational symmetry in the observed diffraction patterns and changes in the strain field reconstructed from ptychography.

Classification and assessment of retrieved electron density maps in coherent X-ray diffraction imaging using multivariate analysis

2016 ◽  
Vol 23 (1) ◽  
pp. 312-323 ◽  
Author(s):  
Yuki Sekiguchi ◽  
Tomotaka Oroguchi ◽  
Masayoshi Nakasako
Keyword(s):  
Diffraction Pattern ◽  
Electron Density ◽  
Phase Retrieval ◽  
Dimensional Space ◽  
X Ray Diffraction ◽  
X Ray ◽  
Density Maps ◽  
Diffraction Imaging ◽  
Density Map ◽  
Electron Density Map

Coherent X-ray diffraction imaging (CXDI) is one of the techniques used to visualize structures of non-crystalline particles of micrometer to submicrometer size from materials and biological science. In the structural analysis of CXDI, the electron density map of a sample particle can theoretically be reconstructed from a diffraction pattern by using phase-retrieval (PR) algorithms. However, in practice, the reconstruction is difficult because diffraction patterns are affected by Poisson noise and miss data in small-angle regions due to the beam stop and the saturation of detector pixels. In contrast to X-ray protein crystallography, in which the phases of diffracted waves are experimentally estimated, phase retrieval in CXDI relies entirely on the computational procedure driven by the PR algorithms. Thus, objective criteria and methods to assess the accuracy of retrieved electron density maps are necessary in addition to conventional parameters monitoring the convergence of PR calculations. Here, a data analysis scheme, named ASURA, is proposed which selects the most probable electron density maps from a set of maps retrieved from 1000 different random seeds for a diffraction pattern. Each electron density map composed ofJpixels is expressed as a point in aJ-dimensional space. Principal component analysis is applied to describe characteristics in the distribution of the maps in theJ-dimensional space. When the distribution is characterized by a small number of principal components, the distribution is classified using thek-means clustering method. The classified maps are evaluated by several parameters to assess the quality of the maps. Using the proposed scheme, structure analysis of a diffraction pattern from a non-crystalline particle is conducted in two stages: estimation of the overall shape and determination of the fine structure inside the support shape. In each stage, the most accurate and probable density maps are objectively selected. The validity of the proposed scheme is examined by application to diffraction data that were obtained from an aggregate of metal particles and a biological specimen at the XFEL facility SACLA using custom-made diffraction apparatus.

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