The use of CCD area detectors in charge-density research. Application to a mineral compound: the α-spodumene LiAl(SiO3)2

1999 ◽  
Vol 55 (6) ◽  
pp. 867-881 ◽  
Author(s):  
Sandrine Kuntzinger ◽  
Slimane Dahaoui ◽  
Nour Eddine Ghermani ◽  
Claude Lecomte ◽  
Judith A. K. Howard
Keyword(s):  
Electron Density ◽  
Silicon Oxide ◽  
Data Sets ◽  
X Ray Diffraction ◽  
Data Set ◽  
Charge Coupled Device ◽  
High Resolution Data ◽  
Aluminosilicate Mineral

X-ray diffraction data sets collected on both Nonius and Siemens (Bruker) goniometers equipped with charge-coupled device (CCD) area detectors have been tested for the electron-density determination of the aluminosilicate mineral compound α-spodumene LiAl(SiO3)2, aluminium lithium silicon oxide. Data collection strategies, reflection intensity peak integration methods and experimental error estimates are different for the two instruments. Therefore, the consistency and quality of the two types of CCD measurements have been carefully compared to each other and to high-resolution data collected on a conventional CAD-4 point-detector diffractometer. Multipole density model refinements were carried out against the CCD data and the statistical factors analysed in terms of experimental weighting schemes based on the standard uncertainties of the diffraction intensities derived by the Nonius and Siemens software programs. Consistent experimental electron-density features in the Si–O–Si and Si–O–Al bridges were found from both CCD data sets. The net atomic charges obtained from the kappa refinements against each CCD data set are also in good agreement and quite comparable with the results of the conventional CAD-4 experiment.

Determination of Optimal Clusters Using a Genetic Algorithm

2008 ◽  
pp. 98-117 ◽  
Author(s):  
Tushar ◽  
Tushar ◽  
Shibendu Shekhar Roy ◽  
Dilip Kumar Pratihar
Keyword(s):  
Genetic Algorithm ◽  
Threshold Value ◽  
Data Sets ◽  
Self Organizing Map ◽  
Data Set ◽  
Fcm Algorithm ◽  
Data Points ◽  
The Relationship

Clustering is a potential tool of data mining. A clustering method analyzes the pattern of a data set and groups the data into several clusters based on the similarity among themselves. Clusters may be either crisp or fuzzy in nature. The present chapter deals with clustering of some data sets using Fuzzy C-Means (FCM) algorithm and Entropy-based Fuzzy Clustering (EFC) algorithm. In FCM algorithm, the nature and quality of clusters depend on the pre-defined number of clusters, level of cluster fuzziness and a threshold value utilized for obtaining the number of outliers (if any). On the other hand, the quality of clusters obtained by the EFC algorithm is dependent on a constant used to establish the relationship between the distance and similarity of two data points, a threshold value of similarity and another threshold value used for determining the number of outliers. The clusters should ideally be distinct and at the same time compact in nature. Moreover, the number of outliers should be as minimum as possible. Thus, the above problem may be posed as an optimization problem, which will be solved using a Genetic Algorithm (GA). The best set of multi-dimensional clusters will be mapped into 2-D for visualization using a Self-Organizing Map (SOM).

Phase perturbation as a means of electron density map quality evaluation

2008 ◽  
Vol 41 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Olga Kirillova
Keyword(s):  
Electron Density ◽  
Data Sets ◽  
Molecular Replacement ◽  
Data Set ◽  
Density Maps ◽  
Phase Perturbation ◽  
Replacement Solution ◽  
Electron Density Map ◽  
Trial Phase

This paper describes a new means for evaluating the quality of crystallographic electron density maps. It has been found that a better data set possesses greater robustness against perturbations applied to the phases. Thus it allows recognition of a more precise phase set and provides a way to select the best or reject the worst from several noisy data sets derived from the same crystal structure. The results indicate that calculation of the correlations by the procedure described here can be useful in ranking electron density maps in this aspect of quality. The method suggested has potential use for selecting a better molecular replacement solution, as well as for evaluating trial phase sets inab initiophasing procedures.

scholarly journals MeshAndCollect: an automated multi-crystal data-collection workflow for synchrotron macromolecular crystallography beamlines

2015 ◽  
Vol 71 (11) ◽  
pp. 2328-2343 ◽  
Author(s):  
Ulrich Zander ◽  
Gleb Bourenkov ◽  
Alexander N. Popov ◽  
Daniele de Sanctis ◽  
Olof Svensson ◽  
...  
Keyword(s):  
Hierarchical Cluster ◽  
Data Sets ◽  
Macromolecular Crystallography ◽  
X Ray Diffraction ◽  
Data Set ◽  
X Ray ◽  
Partial Data ◽  
Final Data ◽  
Dispersion Technique

Here, an automated procedure is described to identify the positions of many cryocooled crystals mounted on the same sample holder, to rapidly predict and rank their relative diffraction strengths and to collect partial X-ray diffraction data sets from as many of the crystals as desired. Subsequent hierarchical cluster analysis then allows the best combination of partial data sets, optimizing the quality of the final data set obtained. The results of applying the method developed to various systems and scenarios including the compilation of a complete data set from tiny crystals of the membrane protein bacteriorhodopsin and the collection of data sets for successful structure determination using the single-wavelength anomalous dispersion technique are also presented.

Determination of depth profiles from X-ray diffraction data

1993 ◽  
Vol 8 (2) ◽  
pp. 122-126 ◽  
Author(s):  
Paul Predecki
Keyword(s):  
Diffraction Data ◽  
Direct Method ◽  
Sample Surface ◽  
Data Sets ◽  
X Ray Diffraction ◽  
Data Set ◽  
X Ray ◽  
Depth Profiles ◽  
A Direct Method

A direct method is described for determining depth profiles (z-profiles) of diffraction data from experimentally determined τ-profiles, where z is the depth beneath the sample surface and τ is the 1/e penetration depth of the X-ray beam. With certain assumptions, the relation between these two profile functions can be expressed in the form of a Laplace transform. The criteria for fitting experimental τ-data to functions which can be utilized by the method are described. The method was applied to two τ-data sets taken from the literature: (1) of residual strain in an A1 thin film and (2) of residual stress in a surface ground A12O3/5vol% TiC composite. For each data set, it was found that the z-profiles obtained were of two types: oscillatory and nonoscillatory. The nonoscillatory profiles appeared to be qualitatively consistent for a given data set. The oscillatory profiles were considered to be not physically realistic. For the data sets considered, the nonoscillatory z-profiles were found to lie consistently above the corresponding τ-profiles, and to approach the τ-profiles at large z, as expected from the relation between the two.

scholarly journals A SELF-ORGANIZING MAP FOR MIXED CONTINUOUS AND CATEGORICAL DATA

2011 ◽  
pp. 24-32 ◽  
Author(s):  
Nicoleta Rogovschi ◽  
Mustapha Lebbah ◽  
Younès Bennani
Keyword(s):  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Mixed Data ◽  
Categorical Variables ◽  
Data Sets ◽  
Self Organizing Map ◽  
Data Set ◽  
Public Data ◽  
Self Organizing

Most traditional clustering algorithms are limited to handle data sets that contain either continuous or categorical variables. However data sets with mixed types of variables are commonly used in data mining field. In this paper we introduce a weighted self-organizing map for clustering, analysis and visualization mixed data (continuous/binary). The learning of weights and prototypes is done in a simultaneous manner assuring an optimized data clustering. More variables has a high weight, more the clustering algorithm will take into account the informations transmitted by these variables. The learning of these topological maps is combined with a weighting process of different variables by computing weights which influence the quality of clustering. We illustrate the power of this method with data sets taken from a public data set repository: a handwritten digit data set, Zoo data set and other three mixed data sets. The results show a good quality of the topological ordering and homogenous clustering.

scholarly journals SPECTROSCOPIC METHODS TO DETERMINATION OF GEOTHITE IN KAOLINITE

2020 ◽  
Vol 17 (35) ◽  
pp. 303-314
Author(s):  
Marcelo Kehl; ; ; ; DE SOUZA ◽  
Marcos Antônio KLUNK ◽  
Soyane Juceli Siqueira XAVIER ◽  
Mohuli DAS ◽  
Sudipta DASGUPTA
Keyword(s):  
Spectroscopic Methods ◽  
Industrial Minerals ◽  
X Ray Diffraction ◽  
Simple Shape ◽  
X Ray ◽  
Spectroscopic Monitoring ◽  
Partial Release ◽  
Primary Minerals

One of the main contaminants of kaolinite, the iron, directly impacts quality in its commercial value. The spectroscopic monitoring, measured the depth of absorption of kaolinite, is compared with the literature in order to identify possible contaminants. The occurrence of kaolinite is due to the formation of primary minerals after the partial release of cations and silicon. This clay-mineral has a simple shape, with variable crystallographic imperfections, especially in the presence of iron, which replaces aluminum in the mineral chain, causing various structural disorganizations. The extraction of industrial minerals combined with geological studies, allows the development of new sources of energy, such as clay minerals, in particular kaolinite. Depending on the origin of the kaolinites, the presence of iron oxides in its structure, Fe2O3 and FeO(OH), are common. By comparing the results of spectroscopy (X-ray fluorescence, X-ray diffraction, RAMAN) and imaging using SEM-EDS, it was possible to identify kaolinite, with a higher determination coefficient, when the proportion of kaolinite reaches 60% or more in the mix. Kaolinite can be identified and quantified with a high correlation in the mixture from the sample absorption. Thus, the method has great potential to assist in quantifying and, consequently, in discriminating the quality of kaolinite.

scholarly journals Influence of the weights in IHS and Brovey methods for pan-sharpening WorldView-3 satellite images

2017 ◽  
Vol 6 (3) ◽  
pp. 71 ◽  
Author(s):  
Claudio Parente ◽  
Massimiliano Pepe
Keyword(s):  
Satellite Images ◽  
Urban Landscape ◽  
Spectral Response ◽  
Rural Landscape ◽  
Spectral Radiance ◽  
Data Sets ◽  
Data Set ◽  
Inertial Moment ◽  
The Impact

The purpose of this paper is to investigate the impact of weights in pan-sharpening methods applied to satellite images. Indeed, different data sets of weights have been considered and compared in the IHS and Brovey methods. The first dataset contains the same weight for each band while the second takes in account the weighs obtained by spectral radiance response; these two data sets are most common in pan-sharpening application. The third data set is resulting by a new method. It consists to compute the inertial moment of first order of each band taking in account the spectral response. For testing the impact of the weights of the different data sets, WorlView-3 satellite images have been considered. In particular, two different scenes (the first in urban landscape, the latter in rural landscape) have been investigated. The quality of pan-sharpened images has been analysed by three different quality indexes: Root mean square error (RMSE), Relative average spectral error (RASE) and Erreur Relative Global Adimensionnelle de Synthèse (ERGAS).

scholarly journals Validation of SCIAMACHY AMC-DOAS water vapour columns

2005 ◽  
Vol 5 (7) ◽  
pp. 1835-1841 ◽  
Author(s):  
S. Noël ◽  
M. Buchwitz ◽  
H. Bovensmann ◽  
J. P. Burrows
Keyword(s):  
Water Vapour ◽  
Visible Spectral Region ◽  
Optical Absorption Spectroscopy ◽  
Data Sets ◽  
Monthly Means ◽  
Data Set ◽  
Weather Forecasts ◽  
Microwave Imager ◽  
Scanning Imaging

Abstract. A first validation of water vapour total column amounts derived from measurements of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) in the visible spectral region has been performed. For this purpose, SCIAMACHY water vapour data have been determined for the year 2003 using an extended version of the Differential Optical Absorption Spectroscopy (DOAS) method, called Air Mass Corrected (AMC-DOAS). The SCIAMACHY results are compared with corresponding water vapour measurements by the Special Sensor Microwave Imager (SSM/I) and with model data from the European Centre for Medium-Range Weather Forecasts (ECMWF). In confirmation of previous results it could be shown that SCIAMACHY derived water vapour columns are typically slightly lower than both SSM/I and ECMWF data, especially over ocean areas. However, these deviations are much smaller than the observed scatter of the data which is caused by the different temporal and spatial sampling and resolution of the data sets. For example, the overall difference with ECMWF data is only -0.05 g/cm2 whereas the typical scatter is in the order of 0.5 g/cm2. Both values show almost no variation over the year. In addition, first monthly means of SCIAMACHY water vapour data have been computed. The quality of these monthly means is currently limited by the availability of calibrated SCIAMACHY spectra. Nevertheless, first comparisons with ECMWF data show that SCIAMACHY (and similar instruments) are able to provide a new independent global water vapour data set.

Weak interactions in chain polymers [M(μ-X)2 L 2]∞ (M = Zn, Cd; X = Cl, Br; L = substituted pyridine) – an electron density study

2009 ◽  
Vol 65 (5) ◽  
pp. 600-611 ◽  
Author(s):  
Ruimin Wang ◽  
Christian W. Lehmann ◽  
Ulli Englert
Keyword(s):  
Hydrogen Bonds ◽  
Electron Density ◽  
Critical Points ◽  
Weak Interactions ◽  
Data Sets ◽  
X Ray Diffraction ◽  
Density Distributions ◽  
The One ◽  
Experimental Electron Density ◽  
Density Study

The experimental electron-density distributions in crystals of five chain polymers [M(μ-X)2(py)2] (M = Zn, Cd; X = Cl, Br; py = 3,5-substituted pyridine) have been obtained from high-resolution X-ray diffraction data sets (sin θ/λ > 1.1 Å−1) at 100 K. Topological analyses following Bader's `Atoms in Molecules' approach not only confirmed the existence of (3, −1) critical points for the chemically reasonable and presumably strong covalent and coordinative bonds, but also for four different secondary interactions which are expected to play a role in stabilizing the polymeric structures which are unusual for Zn as the metal center. These weaker contacts comprise intra- and inter-strand C—H...X—M hydrogen bonds on the one hand and C—X...X—C interhalogen contacts on the other hand. According to the experimental electron-density studies, the non-classical hydrogen bonds are associated with higher electron density in the (3, −1) critical points than the halogen bonds and hence are the dominant interactions both with respect to intra- and inter-chain contacts.

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