Diffraction indexing data

X-Ray Diffraction Analysis. X-ray powder diffraction data for indexing were obtained with a General Electric XRD-6 diffractometer. Samples were sealed in glass capillaries (0.5 mm o.d.) and exposed to nickel-filtered CuKa radiation. KCl or iridium was used as an internal standard. X-ray powder diffraction intensity data were obtained with a General Electric XRD-5 unit. Here,... 

The assumption of different degrees of order between polymers having odd or even numbers of methylene units in die spacer is verified by the X-ray diffraction patterns shown in Figure 7. Crystallinity index data were determined on the basis of these diffraction patterns and the data are presented in Table I. The crystallinity index was calculated according to Equation 1, in which Ac is the area of the sharp Bragg reflections corresponding to the crystalline part of the polymer, and Aa is the area of the broad amorphous peak. 

Unique information about the unit cell in quasi-crystaUine monolayers can be obtained from X-ray °, neutron , heUum or low energy electron diffraction (LEED) data. In the grazing incidence X-ray diffraction (GIXD) experiment the beam is directed at the coated surface at a low angle and experiences total internal reflection from the metal support underneath the monolayer. The analysis of reflectivity and diffraction pattern of this reflected beam provides information about the molecular structure of the crystalline films, the thickness and refractive index of the layers and the roughness of the surface s . These experiments, however, require sophisticated and expensive equipment and are not therefore used routinely for monolayer characterization. 

The resulting blue-black pellet is characterized by X-ray powder diffraction. The indexed data are listed below ... 

The physical data index summarizes the quantitative data given for specific compounds in the text, tables and figures in Volumes 1-7. It does not give any actual data but includes references both to the appropriate text page and to the original literature. The structural and spectroscopic methods covered include UV, IR, Raman, microwave, MS, PES, NMR, ORD, CD, X-ray, neutron and electron diffraction, together with such quantities as dipole moment, pX a, rate constant and activation energy, and equilibrium constant. 

JCPDS-ICDD Elemental and Lattice Spacing Index ilDDO). This index is available from JCPDS-International Centre for Diffraction Data, 1601 Park Lane Swarthmore, PA 19081. 

X-Ray diffraction data have been used to study the aromaticity of complex quinolizinium systems, such as the acenaphtho[4,5-c]quinolizinium derivative 36. The rings connected to the molecule by single C-C bonds are more aromatic than those connected by more links as indicated by the homeostatic model assessment (HOMA) aromaticity index <1992AXC2238>. 

Recent developments and prospects of these methods have been discussed in a chapter by Schneider et al. (2001). It was underlined that these methods are widely applied for the characterization of crystalline materials (phase identification, quantitative analysis, determination of structure imperfections, crystal structure determination and analysis of 3D microstructural properties). Phase identification was traditionally based on a comparison of observed data with interplanar spacings and relative intensities (d and T) listed for crystalline materials. More recent search-match procedures, based on digitized patterns, and Powder Diffraction File (International Centre for Diffraction Data, USA.) containing powder data for hundreds of thousands substances may result in a fast efficient qualitative analysis. The determination of the amounts of different phases present in a multi-component sample (quantitative analysis) is based on the so-called Rietveld method. Procedures for pattern indexing, structure solution and refinement of structure model are based on the same method. 

To determine the phase properties of the calcined bimetallic nanoparticles, a detailed x-ray diffraction (XRD) study was carried out. The XRD data of AuPt/C showed that the diffraction patterns for the carbon-supported nanoparticles show a series of broad Bragg peaks, a picture typical for materials of limited structural coherence. Nevertheless, the peaks are defined well enough to allow a definitive phase identification and structural characterization. The diffraction patterns of Au/C and Pt/C could be unambiguously indexed into an fcc-type cubic lattice occurring with bulk gold and platinum. We estimated the corresponding lattice parameters by carefully determining... 

Almost all crystals suitable for X-ray powder diffraction can be studied by electron diffraction. Several of the most demanding problems with powder diffraction are overcome by electron diffraction. There is no problem of overlapping reflections in electron diffraction and all diffraction spots can be unambiguously indexed. There is no problem of underdetermination (less data than unknown parameters) for electron diffraction since 10-100 times more reflections than parameters can be obtained by ED, whereas in X-ray powder diffraction the over-determination is close to one. 

Electron crystallography of textured samples can benefit from the introduction of automatic or semi-automatic pattern indexing methods for the reconstruction of the three-dimensional reciprocal lattice from two-dimensional data and fitting procedures to model the observed diffraction pattern. Such automatic procedures had not been developed previously, but it is the purpose of this study to develop them now. All these features can contribute to extending the limits of traditional applications such as identification procedures, structure determination etc. 

The main purpose of extracting the diffraction information from any kind of diffraction pattern is to continue with stmcture solution using the extracted quantitative data. This data includes the calculated unit cell parameters obtained during the indexing procedure, s mimetry determination such as a space group or a set of possible space groups and integrated intensities for indexed reflections. 

The indexing proeedure of any diffraction pattern requires the knowledge of positions of some reflections on the pattern. The relations between the position of each peak on a two-dimensional diffraction pattern and the corresponding point in reciprocal space can be established only after a successful indexing. The combined use of the reciprocal coordinates and the determined peak-shape are essential for extracting integrated intensities from diffraction data. 

Note that the number of diffraction peaks decreases with time as the droplet diameter decreases, and the number density of peaks is very nearly proportional to the droplet size. The intensity of the scattered light also decreases with size. The resolution of the photodiode array is not adequate to resolve the fine structure that is seen in Fig. 21, but comparison of the phase functions shown in Fig. 22 with Mie theory indicates that the size can be determined to within 1% without taking into account the fine structure. In this case, however, the results are not very sensitive to refractive index. Some information is lost as the price of rapid data acquisition. 

ELVES has been developed as an expert system, by James Holton and Tom Alber, to go from data collection frames to structure without human intervention and will obviate the need for intermediate space-group determination described above. Very recently, 12 different European sites have been collaborating to develop a software package known as DNA (automateD collectioN of datA) for the automatic collection and indexing of macromolecular diffraction data. Further information is available at the web site www.dna.ac.uk. 

Automatic diffraction analysis is available through the Diffraction Image Screening Tool and Library (DISTL) (Zhang et al., 2006). DISTL incorporates automatic indexing and identification of extraneous features such as ice rings, and provides an estimate of the resolution of the diffraction data. Neural networks have also been tested for the evaluation of crystal quality (Berntson et al., 2003). 

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