scholarly journals Factor Analysis of XRF and XRPD Data on the Example of the Rocks of the Kontozero Carbonatite Complex (NW Russia). Part I: Algorithm

Crystals ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 874
Author(s):  
Ekaterina Fomina ◽  
Evgeniy Kozlov ◽  
Ayya Bazai
Keyword(s):  
Factor Analysis ◽  
Original Method ◽  
Carbonatite Complex ◽  
X Ray ◽  
Mineral Phases ◽  
Diffraction Patterns ◽  
Sample Set ◽  
Geological Research ◽  
Representative Samples ◽  
Selection Of

This paper aims to develop a principle for selecting the most informative samples for geological research from extensive collections of rock material. As a tool for this selection, we chose an original method of statistical comparison of X-ray powder diffraction (XRPD) and X-ray fluorescence (XRF) data using factor analysis (FA). A collection of carbonatites and aluminosilicate rocks from the Kontozero Devonian carbonatite paleovolcano complex (198 samples) is presented to test our technique. The factors extracted during FA were successfully mineralogically interpreted according to peak positions on the graphs of factor loadings. For the studied rock collection, this approach allowed us to identify more than 20 rock-forming minerals based only on XRPD data. We also found about ten mineral phases, the lines of which are low-intensity, and/or which overlap with more intense peaks of other minerals in the diffraction patterns. The mineralogical interpretation of the factors of such hidden minerals can be performed through electron probe microanalysis (EPMA) of the samples previously selected using FA. In this study, we report on an algorithm that facilitates the selection of the rock samples exhibiting the greatest contrast in mineral and chemical composition and which contain the entire set of mineral phases occurring in the geological object under study. From the collection of Kontozero rocks we examined, the 30 most representative samples were selected, amounting to about 15% of the initial sample set.

scholarly journals Solidified Fillings of Nanopores

2005 ◽  
Vol 876 ◽  
Author(s):  
Patrick Huber ◽  
Klaus Knorr
Keyword(s):  
Pore Diameter ◽  
Stacking Faults ◽  
Pore Geometry ◽  
X Ray Diffraction ◽  
X Ray ◽  
Medium Length ◽  
Close Packed Structure ◽  
Packed Structure ◽  
Diffraction Patterns ◽  
Selection Of

AbstractWe present a selection of x-ray diffraction patterns of spherical (He, Ar), dumbbell- (N2, CO), and chain-like molecules (n-C9H20, n-C19H40) solidified in nanopores of silica glass (mean pore diameter 7nm). These patterns allow us to demonstrate how key principles governing crystallization have to be adapted in order to accomplish solidification in restricted geometries. 4He, Ar, and the spherical close packed phases of CO and N2 adjust to the pore geometry by introducing a sizeable amount of stacking faults. For the pore solidified, medium-length chainlike n-C19H40 we observe a close packed structure without lamellar ordering, whereas for the short-chain C9H20 the layering principle survives, albeit in a modified fashion compared to the bulk phase.

PreDICT: a graphical user interface to the DICVOL14 indexing software program for powder diffraction data

2019 ◽  
Vol 34 (3) ◽  
pp. 233-241 ◽  
Author(s):  
Justin R. Blanton ◽  
Robert J. Papoular ◽  
Daniel Louër
Keyword(s):  
Powder Diffraction ◽  
Laboratory Data ◽  
Graphical Interface ◽  
Powder Diffraction Data ◽  
X Ray ◽  
Moderate Number ◽  
Diffraction Patterns ◽  
User Friendly ◽  
Recent Version ◽  
Selection Of

A straightforward intuitive user-friendly compact graphical interface, PreDICT (Premier DICVOL Tool) has been developed to take full advantage of the new capabilities of the most recent version of the DICVOL14 Indexing Software. The latter, an updated version of DICVOL04, includes optimizations, e.g. for monoclinic and triclinic cases, a detailed review of the input data from the indexing solutions, cell centering tests, as well as the handling of a moderate number of impurity peaks. Among the most salient features of PreDICT, one can mention the ability (1) to use 2θ non-equistepped input 1D X-ray powder diffraction patterns as can be obtained from 2D detectors, (2) to strip laboratory data from its Kα2 contribution when present, (3) to generate 2θ equistepped output 1D X-ray powder diffraction patterns in both the “.XY” and “.GSA” formats. In addition, PreDICT allows for the following features: (1) full access to the native DICVOL14 input/output ASCII file system is retained, (2) for any selection of a DICVOL14 suggested unit cell, all predicted Bragg peaks up to a certain 2θMAX value are clearly displayed and indicated, thereby emphasizing the contribution of the unaccounted peaks (if any) to the 1D X-ray powder diffraction pattern under current investigation.

scholarly journals Iron-containing phases in metallurgical and coke dusts as well as in bog iron ore

Nukleonika ◽  
2017 ◽  
Vol 62 (2) ◽  
pp. 187-195 ◽  
Author(s):  
Tadeusz Szumiata ◽  
Marzena Rachwał ◽  
Tadeusz Magiera ◽  
Katarzyna Brzózka ◽  
Małgorzata Gzik-Szumiata ◽  
...  
Keyword(s):  
Magnetic Susceptibility ◽  
Spinel Structure ◽  
Iron Ore ◽  
X Ray Diffraction ◽  
X Ray ◽  
Mineral Phases ◽  
Coke Plants ◽  
Wide Range ◽  
Specific Magnetic Susceptibility ◽  
Diffraction Patterns

Abstract Several samples of dusts from steel and coke plants (collected mostly with electro filters) were subjected to the investigation of content of mineral phases in their particles. Additionally, sample of bog iron ore and metallurgical slurry was studied. Next, the magnetic susceptibility of all the samples was determined, and investigations of iron-containing phases were performed using transmission Mössbauer spectrometry. The values of mass-specific magnetic susceptibility χ varied in a wide range: from 59 to above 7000 × 10−8 m-3·kg−1. The low values are determined for bog iron ore, metallurgical slurry, and coke dusts. The extremely high χ was obtained for metallurgical dusts. The Mössbauer spectra and X-ray diffraction patterns point to the presence of the following phases containing iron: hematite and oxidized magnetite (in coke and metallurgical dusts as well as metallurgical slurry), traces of magnetite fine grains fraction (in metallurgical dusts), amorphous glassy silicates with paramagnetic Fe3+ and Fe2+ ions, traces of pyrrhotite (in coke dusts), α-Fe and nonstoichiometric wüstite (in metallurgical slurry), as well as ferrihydrite nanoparticles (in bog iron ore). For individual samples of metallurgical dusts, the relative contributions of Fe2+/3+ ions in octahedral B sites and Fe2+ ions in tetrahedral A sites in magnetite spinel structure differs considerably.

scholarly journals Aspects of direct phasing in femtosecond nanocrystallography

2014 ◽  
Vol 369 (1647) ◽  
pp. 20130498 ◽  
Author(s):  
Rick P. Millane ◽  
Joe P. J. Chen
Keyword(s):  
Free Electron Laser ◽  
Phase Retrieval ◽  
Laser Diffraction ◽  
Intensity Data ◽  
Noise Levels ◽  
Signal To Noise ◽  
X Ray ◽  
Unit Cells ◽  
Diffraction Patterns ◽  
Selection Of

X-ray free-electron laser diffraction patterns from protein nanocrystals provide information on the diffracted amplitudes between the Bragg reflections, offering the possibility of direct phase retrieval without the use of ancillary experimental data. Proposals for implementing direct phase retrieval are reviewed. These approaches are limited by the signal-to-noise levels in the data and the presence of different and incomplete unit cells in the nanocrystals. The effects of low signal to noise can be ameliorated by appropriate selection of the intensity data samples that are used. The effects of incomplete unit cells may be small in some cases, and a unique solution is likely if there are four or fewer molecular orientations in the unit cell.

scholarly journals AN APPLICATION OF TARGET TRANSFORMATION FACTOR ANALYSIS TO X-RAY DIFFRACTION PATTERNS

1991 ◽  
Vol 7 (Supple) ◽  
pp. 1351-1354
Author(s):  
YGNG KYUN SHIN ◽  
SEUNGWON KIM ◽  
CHUL LEE
Keyword(s):  
Factor Analysis ◽  
X Ray Diffraction ◽  
X Ray ◽  
Transformation Factor ◽  
Diffraction Patterns

Ore characterization by digital color x-ray mapping

1986 ◽  
Vol 44 ◽  
pp. 850-851
Author(s):  
D.S. DeMiglio
Keyword(s):  
Color Image ◽  
Extraction Process ◽  
Color Image Processing ◽  
Silver Particles ◽  
Representative Sampling ◽  
X Ray ◽  
Mineral Phases ◽  
Ore Characterization ◽  
Selection Of ◽  
Scanning Electron

A silver ore was examined by scanning electron microscopy (SEM) to aid in the selection of an extraction process by documenting the distribution and association of elements found within a representative sampling of ore particles. Through the use of color image processing similar to that used by Krakow digital X-ray maps were acquired which showed elemental distributions indicative of mineral phases previously identified by X-ray powder diffraction. Prior to this investigation silver particles (<10 microns) were observed to be randomly distributed throughout the host rock which was primarily a silica gangue.

Rietveld Analysis of Ceramic Nuclear Waste Forms

1993 ◽  
Vol 333 ◽  
Author(s):  
T.J. White ◽  
H. Mitamura
Keyword(s):  
Rietveld Method ◽  
Amorphous Material ◽  
Rietveld Analysis ◽  
X Ray Diffraction ◽  
X Ray ◽  
Waste Forms ◽  
Simulated Waste ◽  
Diffraction Patterns ◽  
Nuclear Waste Forms ◽  
Selection Of

ABSTRACTPowder X-ray diffraction patterns were collected from three titanate waste forms - a calcine powder, a prototype ceramic without waste, and a ceramic containing 10 wt% JW-A simulated waste - and interpreted quantitatively using the Rietveld method. The calcine consisted of fluorite, pyrochlore, rutile, and amorphous material. The prototype waste form contained rutile, hollandite, zirconolite and perovskite. The phase constitution of the JW-A ceramic was freudenbergite, loveringite, hollandite, zirconolite, perovskite and baddeleyite. Procedures for the collection of X-ray data are described, as are assumptions inherent in the Rietveld approach. A selection of refined crystal data are presented.

scholarly journals Factor Analysis of XRF and XRPD Data on the Example of the Rocks of the Kontozero Carbonatite Complex (NW Russia). Part II: Geological Interpretation

Crystals ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 873
Author(s):  
Evgeniy Kozlov ◽  
Ekaterina Fomina ◽  
Pavel Khvorov
Keyword(s):  
Factor Analysis ◽  
Principal Component ◽  
Geochemical Evolution ◽  
Geochemical Data ◽  
Numerical Comparison ◽  
Factor Scores ◽  
Carbonatite Complex ◽  
Geological Interpretation ◽  
Diffraction Patterns ◽  
Potential Use

Numerical comparison of mineralogical and geochemical data, which is required in a variety of geological applications, is a challenging task, especially when analyzing extensive sample collections. Herein, we apply factor analysis (FA) to a collection of 198 diffraction patterns of bulk rock samples from the Kontozero carbonatite complex. The mineralogical information hidden in the X-ray powder diffraction (XRPD) data is thereby squeezed down to a set of two dozen variables represented by factor scores (FS). The values of these FSs show a functional relationship with the contents of the minerals composing the rocks. Therefore, factor scores can be considered as a beneficial tool for rapid qualitative and semiquantitative analysis of the mineral composition of rocks. Supplementing principal component analysis (PCA) with FSs as independent variables characterizing the mineral content of rocks allows for the numerical comparison of mineralogical and geochemical data. By PCA, we reveal the main trends in the mineralogical and geochemical evolution of the investigated rocks of the Kontozero complex. Furthermore, the results are obtained in the very first stages of the research. This fact elucidates the potential use of the proposed technique in geological studies and mining.

Evaluation of Freezing Methods by Low Temperature X-Ray Diffraction

1977 ◽  
Vol 35 ◽  
pp. 330-333
Author(s):  
T. Gulik-Krzywicki ◽  
M.J. Costello
Keyword(s):  
Biological Materials ◽  
Molecular Organization ◽  
X Ray Diffraction ◽  
Glass Capillary ◽  
X Ray ◽  
Rate Dependent ◽  
Before And After ◽  
Freeze Etching ◽  
Diffraction Patterns ◽  
Set Up

Freeze-etching electron microscopy is currently one of the best methods for studying molecular organization of biological materials. Its application, however, is still limited by our imprecise knowledge about the perturbations of the original organization which may occur during quenching and fracturing of the samples and during the replication of fractured surfaces. Although it is well known that the preservation of the molecular organization of biological materials is critically dependent on the rate of freezing of the samples, little information is presently available concerning the nature and the extent of freezing-rate dependent perturbations of the original organizations. In order to obtain this information, we have developed a method based on the comparison of x-ray diffraction patterns of samples before and after freezing, prior to fracturing and replication.Our experimental set-up is shown in Fig. 1. The sample to be quenched is placed on its holder which is then mounted on a small metal holder (O) fixed on a glass capillary (p), whose position is controlled by a micromanipulator.

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