scholarly journals Determination of crystal size distribution by two-dimensional X-ray diffraction

2014 ◽  
Vol 70 (a1) ◽  
pp. C1131-C1131
Author(s):  
Alejandro Rodriguez-Navarro ◽  
Krzysztof Kudłacz
Keyword(s):  
Size Distribution ◽  
Crystal Size ◽  
High Sensitivity ◽  
Crystal Size Distribution ◽  
Polycrystalline Materials ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Area Detector ◽  
Diffraction Patterns

Polycrystalline materials properties and behaviour are ultimately determined by their crystallinity, phase composition and microstructure (i.e., crystal size, preferential orientation). Two-dimensional (2D) diffraction patterns collected with an area detector (i.e., CDD), available in modern X-ray diffractometers, contain detailed information about all these important material characteristics. Furthermore, recent advances in detector technologies permits the collection of high resolution diffraction patterns in which the microstructure of the material can be directly imaged. If the size of beam relative to the crystal size in the sample is adequately choosen, the diffraction pattern produced will have spotty rings in which the spots are the diffracted images of individual grains. The resolution of the image is mainly dependent on the characteristics of the X-ray beam (i.e., diameter, angular divergence), which can be modulated by X-ray optics, sample to detector distance, the pixel size of the detector and the sharpness of the point spread function. From these patterns, the crystal size distribution of different crystalline phases present in the sample can be independently determined using specialized software capable of extracting and combining the information contained in these patterns. This technique is applicable to materials with crystal sizes ranging from submicron to mm sizes and is complementary to techniques based on peak profile analyses (i.e., Scherrer method) which are applicable only to nanocrystalline materials. Finally, given the high sensitivity of current detectors, crystal size evolution can be followed in real-time to study important transformation processes such as crystallization, annealing, etc. The use of 2D X-ray diffraction as applied to microstructure characterization will be illustrated through several examples.

A fast X-ray-diffraction-based method for the determination of crystal size distributions (FXD-CSD)

2018 ◽  
Vol 51 (5) ◽  
pp. 1352-1371 ◽  
Author(s):  
Sigmund H. Neher ◽  
Helmut Klein ◽  
Werner F. Kuhs
Keyword(s):  
Size Distribution ◽  
Chemical Engineering ◽  
Crystal Size ◽  
Crystal Size Distribution ◽  
Polycrystalline Materials ◽  
Distribution Analysis ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Intensity Scaling

A procedure for a fast X-ray-diffraction-based crystal size distribution analysis, named FXD-CSD, is presented. The method enables the user, with minimal sample preparation, to determine the crystal size distribution (CSD) of crystalline powders or polycrystalline materials, derivedviaan intensity scaling procedure from the diffraction intensities of single Bragg spots measured in spotty diffraction patterns with a two-dimensional detector. The method can be implemented on any single-crystal laboratory diffractometer and any synchrotron-based instrument with a fast-readout two-dimensional detector and a precise sample scanning axis. The intensity scaling is achievedviathe measurement of areferencesample with known CSD under identical conditions; the only other prerequisite is that the structure (factors) of bothsampleandreferencematerial must be known. The data analysis is done with a software package written in Python. A detailed account is given of each step of the procedure, including the measurement strategy and the demands on the spottiness of the diffraction rings, the data reduction and the intensity corrections needed, and the data evaluation and the requirements for the reference material. Using commercial laboratory X-ray equipment, several corundum crystal size fractions with precisely known CSD were measured and analysed to verify the accuracy and precision of the FXD-CSD method; a comparison of known and deduced CSDs shows good agreement both in mean size and in the shape of the size distribution. For the used material and diffractometer setup, the crystal size application range is one to several tens of micrometres; this range is highly material and X-ray source dependent and can easily be extended on synchrotron sources to cover the range from below 0.5 µm to over 100 µm. FXD-CSD has the potential to become a generally applicable method for CSD determination in the field of materials science and pharmaceutics, including development and quality management, as well as in various areas of fundamental research in physics, chemistry, chemical engineering, crystallography, the geological sciences and bio-crystallization. It can be used also underin situconditions for studying crystal coarsening phenomena, and delivers precise and accurate CSDs, permitting experimental tests of various theories developed to predict their evolution.

XRD2DScan: new software for polycrystalline materials characterization using two-dimensional X-ray diffraction

2006 ◽  
Vol 39 (6) ◽  
pp. 905-909 ◽  
Author(s):  
Alejandro B. Rodriguez-Navarro
Keyword(s):  
Polycrystalline Materials ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Area Detector ◽  
Multiple Data ◽  
Different Types ◽  
Ψ Angle ◽  
Data Files ◽  
Diffraction Patterns

XRD2DScanis a Windows application for displaying and analyzing two-dimensional X-ray diffraction patterns collected with an area detector. This software allows users to take full advantage of diffractometers that are equipped with an area detector but that cannot readily process the information contained in diffraction patterns from polycrystalline materials.XRD2DScanhas many capabilities for generating different types of scans (2θ scan, ψ scan,dspacingversusψ angle), which allows users to extract the maximum amount of information from two-dimensional patterns. Analyses of multiple data files can be fully automated using batch processing. The use of the software is illustrated through several examples.

Rapid small-angle X-ray diffraction of a tonically contracting molluscan smooth muscle recorded with imaging plates

1989 ◽  
Vol 22 (1) ◽  
pp. 72-74 ◽  
Author(s):  
Y. Tajima ◽  
K. Okada ◽  
O. Yoshida ◽  
T. Seto ◽  
Y. Amemiya
Keyword(s):  
Small Angle ◽  
Structural Changes ◽  
High Sensitivity ◽  
Imaging Plate ◽  
Layer Line ◽  
X Ray Diffraction ◽  
Thin Filaments ◽  
X Ray ◽  
Area Detector ◽  
Diffraction Patterns

Small-angle X-ray diffraction patterns from the anterior byssus retractor muscles of Mytilus edulis contracting tonically in response to stimulation with acetylcholine were recorded in a 30 s exposure with synchrotron radiation and a high-sensitivity X-ray area detector called an imaging plate. The 190 Å layer line from the thin filaments increased in intensity with increase in tonic tension up to 6 x 104 kg m−2. Above this value, the layer-line intensity remained almost constant and comparable to that for a contracting skeletal muscle, indicating that the same structural changes of the thin filaments occur in both muscles.

X-Ray Diffraction

2021 ◽  
pp. 408-480
Author(s):  
Kannan M. Krishnan
Keyword(s):  
Point Group ◽  
Polycrystalline Materials ◽  
X Rays ◽  
X Ray Diffraction ◽  
Symmetry Point Group ◽  
X Ray ◽  
Atomic Scattering ◽  
Scattering Factor ◽  
Diffraction Patterns ◽  
Lattice Planes

X-rays diffraction is fundamental to understanding the structure and crystallography of biological, geological, or technological materials. X-rays scatter predominantly by the electrons in solids, and have an elastic (coherent, Thompson) and an inelastic (incoherent, Compton) component. The atomic scattering factor is largest (= Z) for forward scattering, and decreases with increasing scattering angle and decreasing wavelength. The amplitude of the diffracted wave is the structure factor, F hkl, and its square gives the intensity. In practice, intensities are modified by temperature (Debye-Waller), absorption, Lorentz-polarization, and the multiplicity of the lattice planes involved in diffraction. Diffraction patterns reflect the symmetry (point group) of the crystal; however, they are centrosymmetric (Friedel law) even if the crystal is not. Systematic absences of reflections in diffraction result from glide planes and screw axes. In polycrystalline materials, the diffracted beam is affected by the lattice strain or grain size (Scherrer equation). Diffraction conditions (Bragg Law) for a given lattice spacing can be satisfied by varying θ or λ — for study of single crystals θ is fixed and λ is varied (Laue), or λ is fixed and θ varied to study powders (Debye-Scherrer), polycrystalline materials (diffractometry), and thin films (reflectivity). X-ray diffraction is widely applied.

Exfoliated single molecular layers of Mn0.8PS3 and Cd0.8PS3

2005 ◽  
Vol 20 (5) ◽  
pp. 1107-1112 ◽  
Author(s):  
R.F. Frindt ◽  
D. Yang ◽  
P. Westreich
Keyword(s):  
Ion Exchange ◽  
Structure Factor ◽  
Single Layer ◽  
Layered Compounds ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Vacancy Ordering ◽  
Diffraction Patterns ◽  
Molecular Layers

The layered compounds MnPS3 and CdPS3 were exfoliated to form single molecular layers of Mn0.8PS3 and Cd0.8PS3 in suspension in water by ion exchange. The x-ray diffraction patterns of the two single-layer suspensions showed profound differences in some of the Bragg peaks, and we demonstrated that the differences are not due to the quality or size of the single layers, but are caused by structure factor modulations of the Warren tail for two-dimensional systems. We also demonstrated that the Cd or Mn vacancies generated in the exfoliation process are not ordered at long range, in contrast to an earlier report of vacancy ordering on intercalated MnPS3.

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.

scholarly journals Removing multiple outliers and single-crystal artefacts from X-ray diffraction computed tomography data

2015 ◽  
Vol 48 (6) ◽  
pp. 1943-1955 ◽  
Author(s):  
Antonios Vamvakeros ◽  
Simon D. M. Jacques ◽  
Marco Di Michiel ◽  
Vesna Middelkoop ◽  
Christopher K. Egan ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Single Crystal ◽  
Tomographic Reconstruction ◽  
Projection Data ◽  
Data Sets ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Patterns ◽  
Tomography Data

This paper reports a simple but effective filtering approach to deal with single-crystal artefacts in X-ray diffraction computed tomography (XRD-CT). In XRD-CT, large crystallites can produce spots on top of the powder diffraction rings, which, after azimuthal integration and tomographic reconstruction, lead to line/streak artefacts in the tomograms. In the simple approach presented here, the polar transform is taken of collected two-dimensional diffraction patterns followed by directional median/mean filtering prior to integration. Reconstruction of one-dimensional diffraction projection data sets treated in such a way leads to a very significant improvement in reconstructed image quality for systems that exhibit powder spottiness arising from large crystallites. This approach is not computationally heavy which is an important consideration with big data sets such as is the case with XRD-CT. The method should have application to two-dimensional X-ray diffraction data in general where such spottiness arises.

Microstructure Characterization Of Calcified Tissues By Xrd Using An Area Detector

2008 ◽  
Vol 1094 ◽  
Author(s):  
Alejandro Rodriguez-Navarro ◽  
Antonio G. Checa
Keyword(s):  
Crystal Size ◽  
Self Organization ◽  
Polycrystalline Materials ◽  
Area Detector ◽  
Mineral Components ◽  
Ordered Assembly ◽  
Diffraction Patterns ◽  
Calcified Tissues ◽  
Textured Materials

AbstractOrganisms can precipitate a wide array of minerals which they use to build calcified tissues (i.e., bone, mollusk shell, eggshell, coccolith) having highly sophisticated microstructures. The disposition of organic and mineral components building these materials is highly organized from the nano- to the millimeter scale. Their ordered assembly implies self-organization processes accorded in space and time, giving rise to highly sophisticated textured materials. The objective of our work is the study of fundamental processes in biomineralization such as self-organization processes and texture control in biomineral crystal aggregates. To study the order in the arrangement of shell making crystals we used area detectors available today in modern X-ray diffractometers. The 2D diffraction patterns, collected using such detectors, contain detailed information not only about the mineralogy but also about the microstructure characteristics of polycrystalline materials – crystal size, stress, crystallinity and crystallographic-texture. For instance, to understand microstructure development in mollusk shells, we use this type of detector to do microdiffraction analyses combined with high resolution SEM in order to follow the ordering mechanisms of crystals making these biomaterials.

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