scholarly journals Application of the mineral liberation analysis (MLA) for extraction of grain size and shape measurements in siliciclastic sedimentary rocks

2018 ◽  
Vol 66 ◽  
pp. 02002
Author(s):  
Joanna Pszonka ◽  
Dariusz Sala
Keyword(s):  
Grain Size ◽  
Computer Software ◽  
Data Sets ◽  
Data Set ◽  
X Ray ◽  
Mineral Liberation ◽  
Gravity Flows ◽  
Backscattered Electron ◽  
Grain Size And Shape ◽  
Liberation Analysis

The mineral liberation analysis setup (MLA) consists of a scanning electron microscope (SEM) - based backscattered electron (BSE) image with an energy dispersive X-ray system (EDX) for elemental analysis and a computer software that integrates images and X-ray identification of minerals and maps their distribution. Thereby, various quantitative and qualitative data sets are collected including grain size distribution and shape parameters such as aspect ratio, shape factor and angularity. Other techniques, e.g. the Gazzi-Dickinson point counting method or frequently questionable image analysis software to extract data for textural analysis are time consuming, strenuous and with limitations that need to be addressed. Significant productivity of the mineral liberation analysis provides statistical representation and thereby stringent arguments to detect and suggest some potential solving in uncertainty and complexity of the submarine gravity flows phenomenon that is extremely difficult to monitor, however volumetrically the most significant processes moving sediments on Earth. The mineral liberation analysis seems to be one of the most suitable method to acquire such data set.

Insight in hydrodynamic properties of submarine flows by the mineral liberation analysis system

2020 ◽  
Author(s):  
Joanna Pszonka
Keyword(s):  
Quantitative Data ◽  
Computer Software ◽  
Mineralogical Composition ◽  
Cost Effective ◽  
Transport Processes ◽  
Hydrodynamic Properties ◽  
X Ray ◽  
Mineral Liberation ◽  
Gravity Flows ◽  
Liberation Analysis

<p>The Mineral Liberation Analysis (MLA) setup is an automated measurement system to provide quantitative data of material features. Originally the MLA system was created and applied to mineralogical and metallurgical processing, however its usage turned out promising for extraction of quantitative data sets in other areas, including sedimentary geology, for example grain size and shape, digital textural maps, porosity, modal mineralogy or mineral associations.</p><p>The system is based on a scanning electron microscope (SEM) with an energy dispersive X-ray (EDX) spectrometer and a computer software:</p><p>(i)        backscattered electron (BSE) image analysis allows to determine grain boundaries and locations for X-ray spectral acquisition,</p><p>(ii)       X-ray spectra allow to classify mineralogical composition of samples by comparison to a library of reference spectra, and</p><p>(iii)     software automates microscope operations and data acquisition.</p><p>The application of the MLA is useful for collecting textural and mineralogical features of siliciclastic sediments, relevant for assessment of hydrodynamic properties of the flows that deposited them. Moreover, this approach seems to be crucial for analysis of the processes governing difficult to monitor submarine gravity flows, one of the most important sediment transport processes on Earth. Non-linear, non-uniform and unsteady dynamics of submarine gravity flows cause uncertainty in understanding of their nature. Usage of the MLA increases productivity, provides significant statistical representation, reduces human errors and bias as well as tedious manual analyses and is cost effective.</p>

A batch-wise non-linear fitting and analysis tool for treating large X-ray diffraction data sets

2006 ◽  
Vol 39 (2) ◽  
pp. 262-266 ◽  
Author(s):  
R. J. Davies
Keyword(s):  
Diffraction Data ◽  
Operation Mode ◽  
Large Data ◽  
Scattering Data ◽  
Data Sets ◽  
Analysis Tool ◽  
Data Set ◽  
X Ray ◽  
Linear Fitting ◽  
Non Linear

Synchrotron sources offer high-brilliance X-ray beams which are ideal for spatially and time-resolved studies. Large amounts of wide- and small-angle X-ray scattering data can now be generated rapidly, for example, during routine scanning experiments. Consequently, the analysis of the large data sets produced has become a complex and pressing issue. Even relatively simple analyses become difficult when a single data set can contain many thousands of individual diffraction patterns. This article reports on a new software application for the automated analysis of scattering intensity profiles. It is capable of batch-processing thousands of individual data files without user intervention. Diffraction data can be fitted using a combination of background functions and non-linear peak functions. To compliment the batch-wise operation mode, the software includes several specialist algorithms to ensure that the results obtained are reliable. These include peak-tracking, artefact removal, function elimination and spread-estimate fitting. Furthermore, as well as non-linear fitting, the software can calculate integrated intensities and selected orientation parameters.

Magnetic Properties of Sputtered Fe-O and Co-O Thin Films

1995 ◽  
Vol 403 ◽  
Author(s):  
D. V. Dimitrov ◽  
A. S. Murthy ◽  
G. C. Hadjipanayis ◽  
C. P. SWANN
Keyword(s):  
Grain Size ◽  
Low Temperatures ◽  
Room Temperature ◽  
Oxide Films ◽  
X Ray Diffraction ◽  
Dc Magnetron Sputtering ◽  
Large Shift ◽  
X Ray ◽  
Grain Size And Shape ◽  
Spherical Grains

AbstractFe-O and Co-O films were prepared by DC magnetron sputtering in a mixture of Ar and O2 gases. By varying the oxygen to argon ratio, oxide films with stoichiometry FeO, Fe3O4, α-Fe2O3, CoO and Co3O4 were produced. TEM studies showed that the Fe – oxide films were polycrystalline consisting of small almost spherical grains, about 10 nm in size. Co-O films had different microstructure with grain size and shape dependent on the amount of oxygen. X-ray diffraction studies showed that the grains in Fe-O films were randomly oriented in contrast to Co-O films in which a <111> texture was observed. Pure FeO and α-Fe2O3 films were found to be superparamagnetic at room temperature but strongly ferromagnetic at low temperatures in contrast to the antiferromagnetic nature of bulk samples. A very large shift in the hysteresis loop, about 3800 Oe, was observed in field cooled Co-CoO films indicating the presence of a large unidirectional exchange anisotropy.

A Ccomparison of sedigraph and pipette methods for soil particle-size analysis

Soil Research ◽  
1993 ◽  
Vol 31 (4) ◽  
pp. 407 ◽  
Author(s):  
GD Buchan ◽  
KS Grewal ◽  
JJ Claydon ◽  
RJ Mcpherson
Keyword(s):  
Particle Size ◽  
New Zealand ◽  
Particle Size Analysis ◽  
Size Analysis ◽  
Data Sets ◽  
Regression Equations ◽  
Total Iron Content ◽  
Data Set ◽  
X Ray ◽  
The Difference

The X-ray attenuation (Sedigraph) method for particle-size analysis is known to consistently estimate a finer size distribution than the pipette method. The objectives of this study were to compare the two methods, and to explore the reasons for their divergence. The methods are compared using two data sets from measurements made independently in two New Zealand laboratories, on two different sets of New Zealand soils, covering a range of textures and parent materials. The Sedigraph method gave systematically greater mass percentages at the four measurement diameters (20, 10, 5 and 2 �m). For one data set, the difference between clay (<2 �m) percentages from the two methods is shown to be positively correlated (R2 = 0.625) with total iron content of the sample, for all but one of the soils. This supports a novel hypothesis that the typically greater concentration of Fe (a strong X-ray absorber) in smaller size fractions is the major factor causing the difference. Regression equations are presented for converting the Sedigraph data to their pipette equivalents.

Charge Density of L-Alanyl-glycyl-L-alanine Based on X-Ray Data Collection Periods from 4 to 130 Hours

2007 ◽  
Vol 62 (5) ◽  
pp. 696-704 ◽  
Author(s):  
Diana Förster ◽  
Armin Wagner ◽  
Christian B. Hübschle ◽  
Carsten Paulmann ◽  
Peter Luger
Keyword(s):  
Synchrotron Radiation ◽  
Low Temperature ◽  
Charge Density ◽  
Data Sets ◽  
Data Set ◽  
X Ray ◽  
Atomic Properties ◽  
Multipole Refinement ◽  
Refinement Strategy ◽  
Experimental Charge Density

Abstract The charge density of the tripeptide L-alanyl-glycyl-L-alanine was determined from three X-ray data sets measured at different experimental setups and under different conditions. Two of the data sets were measured with synchrotron radiation (beamline F1 of Hasylab/DESY, Germany and beamline X10SA of SLS, Paul-Scherer-Institute, Switzerland) at temperatures around 100 K while a third data set was measured under home laboratory conditions (MoKα radiation) at a low temperature of 20 K. The multipole refinement strategy to derive the experimental charge density was the same in all cases, so that the obtained charge density properties could directly be compared. While the general analysis of the three data sets suggested a small preference for one of the synchrotron data sets (Hasylab F1), a comparison of topological and atomic properties gave in no case an indication for a preference of any of the three data sets. It follows that even the 4 h data set measured at the SLS performed equally well compared to the data sets of substantially longer exposure time.

In Situ Diffraction Studies: Thermal Decomposition of a Natural Plumbojarosite and the Development of Rietveld-Based Data Analysis Techniques

2010 ◽  
Vol 651 ◽  
pp. 37-64 ◽  
Author(s):  
Ian C. Madsen ◽  
Ian E. Grey ◽  
Stuart J. Mills
Keyword(s):  
Thermal Decomposition ◽  
Amorphous Material ◽  
Data Sets ◽  
X Ray Diffraction ◽  
Data Set ◽  
X Ray ◽  
Analysis Techniques ◽  
Path Lengths ◽  
Instrument Configuration

A study of the thermal decomposition sequence of a sample of natural arsenian plumbojarosite has been undertaken using in situ X-ray diffraction. The sample was heated to 900°C using an Anton-Paar heating stage fitted to an INEL CPS120 diffractometer. The data were analysed using a whole-pattern, Rietveld based approach for the extraction of quantitative phase abundances. The instrument configuration used required the development and application of algorithms to correct for aberrations in the (i) peak intensities due to differing path lengths of incident and diffracted beams in the sample and (ii) peak positions due to sample displacement. Details of the structural models used were refined at selected steps in the pattern and then fixed for subsequent analysis. The data sequence consists of some 110 individual data sets which were analysed sequentially with the output of each run forming the input for analysis of the next data set. The results of the analysis show a complex breakdown and recrystallisation sequence including the formation of a major amount of amorphous material after initial breakdown of the plumbojarosite.

scholarly journals Quantifying instrument errors in macromolecular X-ray data sets

2010 ◽  
Vol 66 (6) ◽  
pp. 733-740 ◽  
Author(s):  
Kay Diederichs
Keyword(s):  
Data Reduction ◽  
Spindle Speed ◽  
Experimental Setup ◽  
Data Sets ◽  
Signal To Noise ◽  
Instrument Error ◽  
Acta Cryst ◽  
Data Set ◽  
X Ray ◽  
The Stability

An indicator which is calculated after the data reduction of a test data set may be used to estimate the (systematic) instrument error at a macromolecular X-ray source. The numerical value of the indicator is the highest signal-to-noise [I/σ(I)] value that the experimental setup can produce and its reciprocal is related to the lower limit of the mergingRfactor. In the context of this study, the stability of the experimental setup is influenced and characterized by the properties of the X-ray beam, shutter, goniometer, cryostream and detector, and also by the exposure time and spindle speed. Typical values of the indicator are given for data sets from the JCSG archive. Some sources of error are explored with the help of test calculations usingSIM_MX[Diederichs (2009),Acta Cryst.D65, 535–542]. One conclusion is that the accuracy of data at low resolution is usually limited by the experimental setup rather than by the crystal. It is also shown that the influence of vibrations and fluctuations may be mitigated by a reduction in spindle speed accompanied by stronger attenuation.

scholarly journals BraggNet: integrating Bragg peaks using neural networks

2019 ◽  
Vol 52 (4) ◽  
pp. 854-863 ◽  
Author(s):  
Brendan Sullivan ◽  
Rick Archibald ◽  
Jahaun Azadmanesh ◽  
Venu Gopal Vandavasi ◽  
Patricia S. Langan ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Negative Control ◽  
Protein Crystal ◽  
Data Sets ◽  
Data Set ◽  
X Ray ◽  
X Ray Crystallography ◽  
Integrated Intensities ◽  
Neutron Crystallography

Neutron crystallography offers enormous potential to complement structures from X-ray crystallography by clarifying the positions of low-Z elements, namely hydrogen. Macromolecular neutron crystallography, however, remains limited, in part owing to the challenge of integrating peak shapes from pulsed-source experiments. To advance existing software, this article demonstrates the use of machine learning to refine peak locations, predict peak shapes and yield more accurate integrated intensities when applied to whole data sets from a protein crystal. The artificial neural network, based on the U-Net architecture commonly used for image segmentation, is trained using about 100 000 simulated training peaks derived from strong peaks. After 100 training epochs (a round of training over the whole data set broken into smaller batches), training converges and achieves a Dice coefficient of around 65%, in contrast to just 15% for negative control data sets. Integrating whole peak sets using the neural network yields improved intensity statistics compared with other integration methods, including k-nearest neighbours. These results demonstrate, for the first time, that neural networks can learn peak shapes and be used to integrate Bragg peaks. It is expected that integration using neural networks can be further developed to increase the quality of neutron, electron and X-ray crystallography data.

scholarly journals Construction of Genetic Linkage Map and QTL Analysis of Sink-Size Traits in Pearl Millet (Pennisetum glaucum)

ISRN Genetics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
V. Vengadessan ◽  
K. N. Rai ◽  
J. R. Kannan Bapu ◽  
C. T. Hash ◽  
R. Bhattacharjee ◽  
...  
Keyword(s):  
Grain Size ◽  
Linkage Map ◽  
Pearl Millet ◽  
Phenotypic Variation ◽  
Mapping Population ◽  
Pennisetum Glaucum ◽  
Data Sets ◽  
Panicle Length ◽  
Data Set ◽  
Sink Size

A linkage map, primarily based on SSCP-SNP markers, was constructed using 188 F2:3 mapping population progenies produced from a cross between two pearl millet inbred lines having diverse parentage. The skeleton linkage map covered 1019 cM and it comprised of 44 markers distributed across the seven linkage groups. Average adjacent-marker intervals ranged from 14 cM on LG1 to 38 cM on LG6, with an overall mean of 23 cM. Using the F2 linkage map and phenotypic data from the F2 and F2:3 generations of the mapping population, a total of 18 putative QTLs were detected for the three sink-size components. Eight QTLs explained 42.7% of observed phenotypic variation for panicle length using the F2:3 data set. For panicle diameter, 5 QTLs explained 45.8% of observed phenotypic variation. Similarly for grain size, 5 QTLs explained 29.6% of phenotypic variation. Genomic regions associated with panicle length, panicle diameter, and grain size were comapped on LG6 between Xpsms88 and Xpsms2270, indicating the existence of a gene or gene cluster. The QTLs for panicle length on LG2 and LG6 (LOD>3 in both F2 and F2:3 data sets), for panicle diameter on LG2 and LG3 (LOD>14 in the F2:3 data set), and for grain size on LG3 and LG6 (LOD>3 in both F2 and F2:3 data sets) were identified as promising candidates for validation prior to possible application in marker-assisted breeding.

scholarly journals The probability distribution of 3D shapes of galaxy clusters from 2D X-ray images

2021 ◽  
Vol 503 (2) ◽  
pp. 2791-2803
Author(s):  
Swapnil Shankar ◽  
Rishi Khatri
Keyword(s):  
Probability Distribution ◽  
Galaxy Clusters ◽  
Galaxy Cluster ◽  
Data Sets ◽  
X Rays ◽  
Data Set ◽  
X Ray ◽  
Individual Object ◽  
3D Shape ◽  
3D Shapes

ABSTRACT We present a new method to determine the probability distribution of the 3D shapes of galaxy clusters from the 2D images using stereology. In contrast to the conventional approach of combining different data sets (such as X-rays, Sunyaev–Zeldovich effect, and lensing) to fit a 3D model of a galaxy cluster for each cluster, our method requires only a single data set, such as X-ray observations or Sunyaev–Zeldovich effect observations, consisting of sufficiently large number of clusters. Instead of reconstructing the 3D shape of an individual object, we recover the probability distribution function (PDF) of the 3D shapes of the observed galaxy clusters. The shape PDF is the relevant statistical quantity, which can be compared with the theory and used to test the cosmological models. We apply this method to publicly available Chandra X-ray data of 89 well-resolved galaxy clusters. Assuming ellipsoidal shapes, we find that our sample of galaxy clusters is a mixture of prolate and oblate shapes, with a preference for oblateness with the most probable ratio of principle axes 1.4 : 1.3 : 1. The ellipsoidal assumption is not essential to our approach and our method is directly applicable to non-ellipsoidal shapes. Our method is insensitive to the radial density and temperature profiles of the cluster. Our method is sensitive to the changes in shape of the X-ray emitting gas from inner to outer regions and we find evidence for variation in the 3D shape of the X-ray emitting gas with distance from the centre.

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