Quantitative Electron Microprobe Analysis Of Semiconductor Materials: An Evaluation Of Accuracy

1999 ◽  
Vol 5 (S2) ◽  
pp. 74-75
Author(s):  
P.K. Carpenter
Keyword(s):  
Ternary Systems ◽  
Data Sets ◽  
Silicate Mineral ◽  
Data Set ◽  
X Ray ◽  
Quantitative Microanalysis ◽  
Wide Range ◽  
Analytical Accuracy ◽  
Unknown Composition ◽  
Counting Statistics

Both precision and accuracy are central to quantitative microanalysis. While precision may be evaluated from x-ray counting statistics and replicate measurement, the determination of analytical accuracy requires well characterized standards of which there are few that span a wide range of compositions in binary and ternary systems. The accuracy of silicate mineral analysis has been previously studied via measurement of α factors at multiple accelerating potential and the subsequent evaluation of correction algorithms and mass absorption coefficient (mac) data sets. This approach has been extended in this study to the In2O3-Ga2O3 and HgTe-CdTe systems.Single crystals of ln2O3, Ga2O3, and an InGa-oxide of unknown composition were used to evaluate accuracy in the In2O3-Ga2O3 binary, using the GaKα, GaLα, and InLα x-ray lines, with WDS measurements performed at 15, 20, and 25KV relative to the ln2O3 and Ga2O3 standards (see Table I). The Ga Kα line exhibits minimal absorption, has no fluorescence correction in this system and is not critically dependent on the correction algorithm or mac data set used.

scholarly journals Poisson errors and adaptive rebinning in X-ray powder diffraction data

2018 ◽  
Vol 33 (4) ◽  
pp. 266-269 ◽  
Author(s):  
Marcus H. Mendenhall
Keyword(s):  
Powder Diffraction ◽  
Diffraction Data ◽  
Data Sets ◽  
Powder Diffraction Data ◽  
Data Set ◽  
X Ray ◽  
Short Summary ◽  
Correct Assignment ◽  
Wide Range ◽  
Diffraction Patterns

This work provides a short summary of techniques for formally-correct handling of statistical uncertainties in Poisson-statistics dominated data, with emphasis on X-ray powder diffraction patterns. Correct assignment of uncertainties for low counts is documented. Further, we describe a technique for adaptively rebinning such data sets to provide more uniform statistics across a pattern with a wide range of count rates, from a few (or no) counts in a background bin to on-peak regions with many counts. This permits better plotting of data and analysis of a smaller number of points in a fitting package, without significant degradation of the information content of the data set. Examples of the effect of this on a diffraction data set are given.

Simultaneous structure refinement of neutron, synchrotron and X-ray powder diffraction patterns

1988 ◽  
Vol 21 (1) ◽  
pp. 22-28 ◽  
Author(s):  
J. K. Maichle ◽  
J. Ihringer ◽  
W. Prandl
Keyword(s):  
Powder Diffraction ◽  
Goodness Of Fit ◽  
Structural Model ◽  
Rietveld Method ◽  
Structure Refinement ◽  
Data Sets ◽  
Data Set ◽  
X Ray ◽  
Counting Statistics ◽  
The Individual

A technique has been developed for the simultaneous analysis of several powder diffraction data on the basis of the Rietveld method. Counting rates from one specimen at a given temperature taken at neutron, synchrotron or X-ray powder diffractometers are joined to one single data set with weights given by the counting statistics. The structure is refined from this data set with a parameter field containing one structural model and individual zero points, scale factors and FWHM parameters for each of the methods and data sets. A new definition of the residuals is given. The residuals and goodness-of-fit values are calculated for all as well as for the individual data sets.

scholarly journals A Visual and VAE Based Hierarchical Indoor Localization Method

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3406
Author(s):  
Jie Jiang ◽  
Yin Zou ◽  
Lidong Chen ◽  
Yujie Fang
Keyword(s):  
Image Retrieval ◽  
Indoor Localization ◽  
Data Sets ◽  
Indoor Environments ◽  
Global Features ◽  
Data Set ◽  
Data Annotation ◽  
Wide Range ◽  
Annotation Costs ◽  
Global And Local

Precise localization and pose estimation in indoor environments are commonly employed in a wide range of applications, including robotics, augmented reality, and navigation and positioning services. Such applications can be solved via visual-based localization using a pre-built 3D model. The increase in searching space associated with large scenes can be overcome by retrieving images in advance and subsequently estimating the pose. The majority of current deep learning-based image retrieval methods require labeled data, which increase data annotation costs and complicate the acquisition of data. In this paper, we propose an unsupervised hierarchical indoor localization framework that integrates an unsupervised network variational autoencoder (VAE) with a visual-based Structure-from-Motion (SfM) approach in order to extract global and local features. During the localization process, global features are applied for the image retrieval at the level of the scene map in order to obtain candidate images, and are subsequently used to estimate the pose from 2D-3D matches between query and candidate images. RGB images only are used as the input of the proposed localization system, which is both convenient and challenging. Experimental results reveal that the proposed method can localize images within 0.16 m and 4° in the 7-Scenes data sets and 32.8% within 5 m and 20° in the Baidu data set. Furthermore, our proposed method achieves a higher precision compared to advanced methods.

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.

scholarly journals Global whole-rock geochemical database compilation

2019 ◽  
Author(s):  
Matthew Gard ◽  
Derrick Hasterok ◽  
Jacqueline Halpin
Keyword(s):  
Database Management ◽  
Temporal Trends ◽  
Physical Property ◽  
Database Management System ◽  
Geochemical Data ◽  
Data Sets ◽  
Unique Contribution ◽  
Data Set ◽  
Wide Range ◽  
Geochemical Indices

Abstract. Dissemination and collation of geochemical data are critical to promote rapid, creative and accurate research and place new results in an appropriate global context. To this end, we have assembled a global whole-rock geochemical database, with other associated sample information and properties, sourced from various existing databases and supplemented with numerous individual publications and corrections. Currently the database stands at 1,023,490 samples with varying amounts of associated information including major and trace element concentrations, isotopic ratios, and location data. The distribution both spatially and temporally is quite heterogeneous, however temporal distributions are enhanced over some previous database compilations, particularly in terms of ages older than ~ 1000 Ma. Also included are a wide range of computed geochemical indices, physical property estimates and naming schema on a major element normalized version of the geochemical data for quick reference. This compilation will be useful for geochemical studies requiring extensive data sets, in particular those wishing to investigate secular temporal trends. The addition of physical properties, estimated by sample chemistry, represents a unique contribution to otherwise similar geochemical databases. The data is published in .csv format for the purposes of simple distribution but exists in a format acceptable for database management systems (e.g. SQL). One can either manipulate this data using conventional analysis tools such as MATLAB®, Microsoft® Excel, or R, or upload to a relational database management system for easy querying and management of the data as unique keys already exist. This data set will continue to grow, and we encourage readers to contact us or other database compilations contained within about any data that is yet to be included. The data files described in this paper are available at https://doi.org/10.5281/zenodo.2592823 (Gard et al., 2019).

scholarly journals Panoramic stitching of heterogeneous single-cell transcriptomic data

2018 ◽  
Author(s):  
Brian Hie ◽  
Bryan Bryson ◽  
Bonnie Berger
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Data Sets ◽  
Cell Type ◽  
Data Set ◽  
Wide Range ◽  
Data Set Integration ◽  
Biological Patterns ◽  
Insight Into ◽  
Comprehensive Reference

AbstractResearchers are generating single-cell RNA sequencing (scRNA-seq) profiles of diverse biological systems1–4 and every cell type in the human body.5 Leveraging this data to gain unprecedented insight into biology and disease will require assembling heterogeneous cell populations across multiple experiments, laboratories, and technologies. Although methods for scRNA-seq data integration exist6,7, they often naively merge data sets together even when the data sets have no cell types in common, leading to results that do not correspond to real biological patterns. Here we present Scanorama, inspired by algorithms for panorama stitching, that overcomes the limitations of existing methods to enable accurate, heterogeneous scRNA-seq data set integration. Our strategy identifies and merges the shared cell types among all pairs of data sets and is orders of magnitude faster than existing techniques. We use Scanorama to combine 105,476 cells from 26 diverse scRNA-seq experiments across 9 different technologies into a single comprehensive reference, demonstrating how Scanorama can be used to obtain a more complete picture of cellular function across a wide range of scRNA-seq experiments.

Characterising RDF data sets

2017 ◽  
Vol 44 (2) ◽  
pp. 203-229 ◽  
Author(s):  
Javier D Fernández ◽  
Miguel A Martínez-Prieto ◽  
Pablo de la Fuente Redondo ◽  
Claudio Gutiérrez
Keyword(s):  
Data Structures ◽  
Large Scale ◽  
Open Data ◽  
Structural Features ◽  
Data Sets ◽  
Data Set ◽  
Wide Range ◽  
Rdf Data ◽  
Description Framework ◽  
Resource Description

The publication of semantic web data, commonly represented in Resource Description Framework (RDF), has experienced outstanding growth over the last few years. Data from all fields of knowledge are shared publicly and interconnected in active initiatives such as Linked Open Data. However, despite the increasing availability of applications managing large-scale RDF information such as RDF stores and reasoning tools, little attention has been given to the structural features emerging in real-world RDF data. Our work addresses this issue by proposing specific metrics to characterise RDF data. We specifically focus on revealing the redundancy of each data set, as well as common structural patterns. We evaluate the proposed metrics on several data sets, which cover a wide range of designs and models. Our findings provide a basis for more efficient RDF data structures, indexes and compressors.

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.

Phosphorus L 2,3-edge XANES: overview of reference compounds

2009 ◽  
Vol 16 (2) ◽  
pp. 247-259 ◽  
Author(s):  
Jens Kruse ◽  
Peter Leinweber ◽  
Kai-Uwe Eckhardt ◽  
Frauke Godlinski ◽  
Yongfeng Hu ◽  
...  
Keyword(s):  
Spectral Features ◽  
Edge Structure ◽  
Complex Samples ◽  
Distinctive Features ◽  
X Ray ◽  
Wide Range ◽  
Element Speciation ◽  
Unknown Composition ◽  
Almost All ◽  
X Ray Absorption

Synchrotron-based X-ray absorption near-edge structure (XANES) spectroscopy is becoming an increasingly used tool for the element speciation in complex samples. For phosphorus (P) almost all XANES measurements have been carried out at the K-edge. The small number of distinctive features at the P K-edge makes in some cases the identification of different P forms difficult or impossible. As indicated by a few previous studies, the P L 2,3-edge spectra were richer in spectral features than those of the P K-edge. However, experimentally consistent spectra of a wide range of reference compounds have not been published so far. In this study a library of spectral features is presented for a number of mineral P, organic P and P-bearing minerals for fingerprinting identification. Furthermore, the effect of radiation damage is shown for three compounds and measures are proposed to reduce it. The spectra library provided lays a basis for the identification of individual P forms in samples of unknown composition for a variety of scientific areas.

The subatomic resolution study of laccase inhibition by chloride and fluoride anions using single-crystal serial crystallography: insights into the enzymatic reaction mechanism

2019 ◽  
Vol 75 (9) ◽  
pp. 804-816 ◽  
Author(s):  
Konstantin M. Polyakov ◽  
Sergei Gavryushov ◽  
Tatiana V. Fedorova ◽  
Olga A. Glazunova ◽  
Alexander N. Popov
Keyword(s):  
Molecular Oxygen ◽  
Enzymatic Reaction ◽  
Copper Ion ◽  
Data Sets ◽  
X Ray Diffraction ◽  
Fluoride Ions ◽  
X Ray ◽  
Mechanism Of Inhibition ◽  
Wide Range ◽  
Oxygen Ligand

Laccases are enzymes that catalyze the oxidation of a wide range of organic and inorganic substrates accompanied by the reduction of molecular oxygen to water. Here, a subatomic resolution X-ray crystallographic study of the mechanism of inhibition of the laccase from the basidiomycete fungus Steccherinum murashkinskyi by chloride and fluoride ions is presented. Three series of X-ray diffraction data sets were collected with increasing doses of absorbed X-ray radiation from a native S. murashkinskyi laccase crystal and from crystals of complexes of the laccase with chloride and fluoride ions. The data for the native laccase crystal confirmed the previously deduced enzymatic mechanism of molecular oxygen reduction. The structures of the complexes allowed the localization of chloride and fluoride ions in the channel near the T2 copper ion. These ions replace the oxygen ligand of the T2 copper ion in this channel and can play the role of this ligand in the enzymatic reaction. As follows from analysis of the structures from the increasing dose series, the inhibition of laccases by chloride and fluoride anions can be explained by the fact that the binding of these negatively charged ions at the position of the oxygen ligand of the T2 copper ion impedes the reduction of the T2 copper ion.

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