scholarly journals Three-dimensional propagation in near-field tomographic X-ray phase retrieval

2016 ◽  
Vol 72 (2) ◽  
pp. 215-221 ◽  
Author(s):  
Aike Ruhlandt ◽  
Tim Salditt
Keyword(s):  
Phase Retrieval ◽  
Near Field ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Current Phase ◽  
Computationally Efficient ◽  
X Ray ◽  
Reconstruction Quality ◽  
Consistency Constraints

This paper presents an extension of phase retrieval algorithms for near-field X-ray (propagation) imaging to three dimensions, enhancing the quality of the reconstruction by exploiting previously unused three-dimensional consistency constraints. The approach is based on a novel three-dimensional propagator and is derived for the case of optically weak objects. It can be easily implemented in current phase retrieval architectures, is computationally efficient and reduces the need for restrictive prior assumptions, resulting in superior reconstruction quality.

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.

Three-dimensional grain resolved strain mapping using laboratory X-ray diffraction contrast tomography: theoretical analysis

2022 ◽  
Vol 55 (1) ◽  
Author(s):  
Adam Lindkvist ◽  
Yubin Zhang
Keyword(s):  
Near Field ◽  
Three Dimensional ◽  
Simulated Data ◽  
Three Dimensions ◽  
X Ray Diffraction ◽  
Strain Mapping ◽  
X Ray ◽  
Microstructural Parameters ◽  
Diffraction Contrast ◽  
Sample Distance

Laboratory diffraction contrast tomography (LabDCT) is a recently developed technique to map crystallographic orientations of polycrystalline samples in three dimensions non-destructively using a laboratory X-ray source. In this work, a new theoretical procedure, named LabXRS, expanding LabDCT to include mapping of the deviatoric strain tensors on the grain scale, is proposed and validated using simulated data. For the validation, the geometries investigated include a typical near-field LabDCT setup utilizing Laue focusing with equal source-to-sample and sample-to-detector distances of 14 mm, a magnified setup where the sample-to-detector distance is increased to 200 mm, a far-field Laue focusing setup where the source-to-sample distance is also increased to 200 mm, and a near-field setup with a source-to-sample distance of 200 mm. The strain resolution is found to be in the range of 1–5 × 10−4, depending on the geometry of the experiment. The effects of other experimental parameters, including pixel binning, number of projections and imaging noise, as well as microstructural parameters, including grain position, grain size and grain orientation, on the strain resolution are examined. The dependencies of these parameters, as well as the implications for practical experiments, are discussed.

scholarly journals Reconstruction of crystal shapes by X-ray nanodiffraction from three-dimensional superlattices

2014 ◽  
Vol 47 (6) ◽  
pp. 2030-2037 ◽  
Author(s):  
Mojmír Meduňa ◽  
Claudiu V. Falub ◽  
Fabio Isa ◽  
Daniel Chrastina ◽  
Thomas Kreiliger ◽  
...  
Keyword(s):  
Structural Model ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Semiconductor Layer ◽  
Dimensional Structure ◽  
Solid State Lasers ◽  
X Ray ◽  
Nondestructive Imaging ◽  
Low Dimensional

Quantitative nondestructive imaging of structural properties of semiconductor layer stacks at the nanoscale is essential for tailoring the device characteristics of many low-dimensional quantum structures, such as ultrafast transistors, solid state lasers and detectors. Here it is shown that scanning nanodiffraction of synchrotron X-ray radiation can unravel the three-dimensional structure of epitaxial crystals containing a periodic superlattice underneath their faceted surface. By mapping reciprocal space in all three dimensions, the superlattice period is determined across the various crystal facets and the very high crystalline quality of the structures is demonstrated. It is shown that the presence of the superlattice allows the reconstruction of the crystal shape without the need of any structural model.

scholarly journals Reconstruction of the near-field distribution in an X-ray waveguide array

2017 ◽  
Vol 50 (3) ◽  
pp. 701-711 ◽  
Author(s):  
Qi Zhong ◽  
Lars Melchior ◽  
Jichang Peng ◽  
Qiushi Huang ◽  
Zhanshan Wang ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Field Distribution ◽  
Phase Retrieval ◽  
Near Field ◽  
Field Pattern ◽  
Waveguide Array ◽  
X Ray ◽  
Field Patterns ◽  
Thickness Variations ◽  
Far Field Pattern

Iterative phase retrieval has been used to reconstruct the near-field distribution behind tailored X-ray waveguide arrays, by inversion of the measured far-field pattern recorded under fully coherent conditions. It is thereby shown that multi-waveguide interference can be exploited to control the near-field distribution behind the waveguide exit. This can, for example, serve to create a secondary quasi-focal spot outside the waveguide structure. For this proof of concept, an array of seven planar Ni/C waveguides are used, with precisely varied guiding layer thickness and cladding layer thickness, as fabricated by high-precision magnetron sputtering systems. The controlled thickness variations in the range of 0.2 nm results in a desired phase shift of the different waveguide beams. Two kinds of samples, a one-dimensional waveguide array and periodic waveguide multilayers, were fabricated, each consisting of seven C layers as guiding layers and eight Ni layers as cladding layers. These are shown to yield distinctly different near-field patterns.

Three-dimensional X-ray diffraction imaging of process-induced dislocation loops in silicon

2011 ◽  
Vol 44 (3) ◽  
pp. 526-531 ◽  
Author(s):  
David Allen ◽  
Jochen Wittge ◽  
Jennifer Stopford ◽  
Andreas Danilewsky ◽  
Patrick McNally
Keyword(s):  
Semiconductor Industry ◽  
Three Dimensional ◽  
Crystal Defects ◽  
Three Dimensions ◽  
Dimensional Structure ◽  
Dislocation Loops ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Imaging ◽  
Relationship Of

In the semiconductor industry, wafer handling introduces micro-cracks at the wafer edge and the causal relationship of these cracks to wafer breakage is a difficult task. By way of understanding the wafer breakage process, a series of nano-indents were introduced both into 20 × 20 mm (100) wafer pieces and into whole wafers as a means of introducing controlled strain. Visualization of the three-dimensional structure of crystal defects has been demonstrated. The silicon samples were then treated by various thermal anneal processes to initiate the formation of dislocation loops around the indents. This article reports the three-dimensional X-ray diffraction imaging and visualization of the structure of these dislocations. A series of X-ray section topographs of both the indents and the dislocation loops were taken at the ANKA Synchrotron, Karlsruhe, Germany. The topographs were recorded on a CCD system combined with a high-resolution scintillator crystal and were measured by repeated cycles of exposure and sample translation along a direction perpendicular to the beam. The resulting images were then rendered into three dimensions utilizing open-source three-dimensional medical tomography algorithms that show the dislocation loops formed. Furthermore this technique allows for the production of a video (avi) file showing the rotation of the rendered topographs around any defined axis. The software also has the capability of splitting the image along a segmentation line and viewing the internal structure of the strain fields.

Still rendering: An exploration of 3D technologies for painting and other conventional mediums

2020 ◽  
Vol 6 (1) ◽  
pp. 53-72 ◽  
Author(s):  
Caitlin Cheek
Keyword(s):  
Three Dimensional ◽  
Three Dimensions ◽  
Traditional Art ◽  
3D Software ◽  
Modern Technologies

Artists working in the field of animation, games and films are expected to have in-depth knowledge of three-dimensional (3D) software as well as traditional art principles. However, when it comes to creating conventional paintings, many artists have yet to use 3D computer imaging. 3D software expands beyond what is possible in other computer programmes such as Photoshop, InDesign or Illustrator by giving the creator access to unlimited potential in three dimensions. My work embraces these modern technologies, crossing the boundaries between new and old media, to inform the paintings I create with oil on canvas. I utilize 3D software to push the surreal yet realistic quality of a setting. In this article, I explore my work in the context of historical precedents and contemporary examples that combine conventional media and 3D computer imaging. Keeping up and creatively employing these technologies within conventional modes of painting presents an opportunity to push the boundaries of my art.

Diffraction by crystals

2002 ◽  
Author(s):  
David Blow
Keyword(s):  
Fourier Transform ◽  
Three Dimensional ◽  
Incident Beam ◽  
Two Dimensions ◽  
Three Dimensions ◽  
Dimensional Structure ◽  
Angle Of Incidence ◽  
X Ray ◽  
Max Von Laue ◽  
The Fourier Transform

In Chapter 4 many two-dimensional examples were shown, in which a diffraction pattern represents the Fourier transform of the scattering object. When a diffracting object is three-dimensional, a new effect arises. In diffraction by a repetitive object, rays are scattered in many directions. Each unit of the lattice scatters, but a diffracted beam arises only if the scattered rays from each unit are all in phase. Otherwise the scattering from one unit is cancelled out by another. In two dimensions, there is always a direction where the scattered rays are in phase for any order of diffraction (just as shown for a one-dimensional scatterer in Fig. 4.1). In three dimensions, it is only possible for all the points of a lattice to scatter in phase if the crystal is correctly oriented in the incident beam. The amplitudes and phases of all the scattered beams from a three-dimensional crystal still provide the Fourier transform of the three-dimensional structure. But when a crystal is at a particular angular orientation to the X-ray beam, the scattering of a monochromatic beam provides only a tiny sample of the total Fourier transform of its structure. In the next section, we are going to find what is needed to allow a diffracted beam to be generated. We shall follow a treatment invented by Lawrence Bragg in 1913. Max von Laue, who discovered X-ray diffraction in 1912, used a different scheme of analysis; and Paul Ewald introduced a new way of looking at it in 1921. These three methods are referred to as the Laue equations, Bragg’s law and the Ewald construction, and they give identical results. All three are described in many crystallographic text books. Bragg’s method is straightforward, understandable, and suffices for present needs. I had heard J.J. Thomson lecture about…X-rays as very short pulses of radiation. I worked out that such pulses…should be reflected at any angle of incidence by the sheets of atoms in the crystal as if these sheets were mirrors.…It remained to explain why certain of the atomic mirrors in the zinc blende [ZnS] crystal reflected more powerfully than others.

Diffraction

2002 ◽  
Author(s):  
David Blow
Keyword(s):  
Red Light ◽  
Three Dimensional ◽  
Three Dimensions ◽  
X Rays ◽  
X Ray ◽  
Original Direction ◽  
Computational Procedures ◽  
Scattering Material ◽  
Opaque Object ◽  
Diffraction Effects

Diffraction refers to the effects observed when light is scattered into directions other than the original direction of the light, without change of wavelength. An X-ray photon may interact with an electron and set the electron oscillating with the X-ray frequency. The oscillating electron may radiate an X-ray photon of the same wavelength, in a random direction, when it returns to its unexcited state. Other processes may also occur, akin to fluorescence, which emit X-rays of longer wavelengths, but these processes do not give diffraction effects. Just as we see a red card because red light is scattered off the card into our eyes, objects are observed with X-rays because an illuminating X-ray beam is scattered into the X-ray detector. Our eye can analyse details of the card because its lens forms an image on the retina. Since no X-ray lens is available, the scattered X-ray beam cannot be converted directly into an image. Indirect computational procedures have to be used instead. X-rays are penetrating radiation, and can be scattered from electrons throughout the whole scattering object, while light only shows the external shape of an opaque object like a red card. This allows X-rays to provide a truly three-dimensional image. When X-rays pass near an atom, only a tiny fraction of them is scattered: most of the X-rays pass further into the object, and usually most of them come straight out the other side of the whole object. In forming an image, these ‘straight through’ X-rays tell us nothing about the structure, and they are usually captured by a beam stop and ignored. This chapter begins by explaining that the diffraction of light or X-rays can provide a precise physical realization of Fourier’s method of analysing a regularly repeating function. This method may be used to study regularly repeating distributions of scattering material. Beginning in one dimension, examples will be used to bring out some fundamental features of diffraction analysis. Graphic examples of two-dimensional diffraction provide further demonstrations. Although the analysis in three dimensions depends on exactly the same principles, diffraction by a three-dimensional crystal raises additional complications.

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 Gold Exploration in Two and Three Dimensions: Improved and Correlative Insights from Microscopy and X-Ray Computed Tomography

Minerals ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 476
Author(s):  
Joshua Chisambi ◽  
Bjorn von der Heyden ◽  
Muofhe Tshibalanganda ◽  
Stephan Le Roux
Keyword(s):  
Computed Tomography ◽  
Spatial Distribution ◽  
Gold Mineralization ◽  
Three Dimensional ◽  
Three Dimensions ◽  
Low Grade ◽  
X Ray ◽  
3D Space ◽  
X Ray Computed ◽  
2D And 3D

In this contribution, we highlight a correlative approach in which three-dimensional structural/positional data are combined with two dimensional chemical and mineralogical data to understand a complex orogenic gold mineralization system; we use the Kirk Range (southern Malawi) as a case study. Three dimensional structures and semi-quantitative mineral distributions were evaluated using X-ray Computed Tomography (XCT) and this was augmented with textural, mineralogical and chemical imaging using Scanning Electron Microscopy (SEM) and optical microscopy as well as fire assay. Our results detail the utility of the correlative approach both for quantifying gold concentrations in core samples (which is often nuggety and may thus be misrepresented by quarter- or half-core assays), and for understanding the spatial distribution of gold and associated structures and microstructures in 3D space. This approach overlays complementary datasets from 2D and 3D analytical protocols, thereby allowing a better and more comprehensive understanding on the distribution and structures controlling gold mineralization. Combining 3D XCT analyses with conventional 2D microscopies derive the full value out of a given exploration drilling program and it provides an excellent tool for understanding gold mineralization. Understanding the spatial distribution of gold and associated structures and microstructures in 3D space holds vast potential for exploration practitioners, especially if the correlative approach can be automated and if the resultant spatially-constrained microstructural information can be fed directly into commercially available geological modelling software. The extra layers of information provided by using correlative 2D and 3D microscopies offer an exciting new tool to enhance and optimize mineral exploration workflows, given that modern exploration efforts are targeting increasingly complex and low-grade ore deposits.

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