Using Similarity Metrics to Quantify Differences in High-Throughput Data Sets: Application to X-ray Diffraction Patterns

2016 ◽  
Vol 19 (1) ◽  
pp. 25-36 ◽  
Author(s):  
Efraín Hernández-Rivera ◽  
Shawn P. Coleman ◽  
Mark A. Tschopp
Keyword(s):  
High Throughput ◽  
Similarity Metrics ◽  
Data Sets ◽  
X Ray Diffraction ◽  
X Ray ◽  
High Throughput Data ◽  
Diffraction Patterns

scholarly journals Removing multiple outliers and single-crystal artefacts from X-ray diffraction computed tomography data

2015 ◽  
Vol 48 (6) ◽  
pp. 1943-1955 ◽  
Author(s):  
Antonios Vamvakeros ◽  
Simon D. M. Jacques ◽  
Marco Di Michiel ◽  
Vesna Middelkoop ◽  
Christopher K. Egan ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Single Crystal ◽  
Tomographic Reconstruction ◽  
Projection Data ◽  
Data Sets ◽  
Two Dimensional ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Patterns ◽  
Tomography Data

This paper reports a simple but effective filtering approach to deal with single-crystal artefacts in X-ray diffraction computed tomography (XRD-CT). In XRD-CT, large crystallites can produce spots on top of the powder diffraction rings, which, after azimuthal integration and tomographic reconstruction, lead to line/streak artefacts in the tomograms. In the simple approach presented here, the polar transform is taken of collected two-dimensional diffraction patterns followed by directional median/mean filtering prior to integration. Reconstruction of one-dimensional diffraction projection data sets treated in such a way leads to a very significant improvement in reconstructed image quality for systems that exhibit powder spottiness arising from large crystallites. This approach is not computationally heavy which is an important consideration with big data sets such as is the case with XRD-CT. The method should have application to two-dimensional X-ray diffraction data in general where such spottiness arises.

Study of diffraction data sets using factor analysis: a new technique for comparing mineralogical and geochemical data and rapid diagnostics of the mineral composition of large collections of rock samples

2019 ◽  
Vol 34 (S1) ◽  
pp. S59-S70 ◽  
Author(s):  
Ekaterina Fomina ◽  
Evgeniy Kozlov ◽  
Svetlana Ivashevskaja
Keyword(s):  
Geochemical Data ◽  
Chemical Compositions ◽  
Data Sets ◽  
Rapid Diagnostics ◽  
X Ray Diffraction ◽  
X Ray ◽  
Short Period ◽  
Diffraction Patterns ◽  
A New Technique

This paper presents an example of comparing geochemical and mineralogical data by means of the statistical analysis of the X-ray diffraction patterns and the chemical compositions of bulk samples. The proposed methodology was tested on samples of metasomatic rocks from two geologically different objects. Its application allows us to mathematically identify all the main, secondary and some accessory minerals, to qualitatively estimate the contents of these minerals, as well as to assess their effect on the distribution of all petrogenic and investigated trace elements in a short period of time at the earliest stages of the research. We found that the interpretation of the results is significantly influenced by the number of samples studied and the quality of diffractograms.

scholarly journals Open and strong-scaling tools for atom-probe crystallography: high-throughput methods for indexing crystal structure and orientation

2021 ◽  
Vol 54 (5) ◽  
pp. 1490-1508
Author(s):  
Markus Kühbach ◽  
Matthew Kasemer ◽  
Baptiste Gault ◽  
Andrew Breen
Keyword(s):  
Crystal Structure ◽  
High Throughput ◽  
Software Tool ◽  
Atom Probe ◽  
Data Sets ◽  
Spatial Correlations ◽  
X Ray Diffraction ◽  
Automated Identification ◽  
X Ray ◽  
Strong Scaling

Volumetric crystal structure indexing and orientation mapping are key data processing steps for virtually any quantitative study of spatial correlations between the local chemical composition features and the microstructure of a material. For electron and X-ray diffraction methods it is possible to develop indexing tools which compare measured and analytically computed patterns to decode the structure and relative orientation within local regions of interest. Consequently, a number of numerically efficient and automated software tools exist to solve the above characterization tasks. For atom-probe tomography (APT) experiments, however, the strategy of making comparisons between measured and analytically computed patterns is less robust because many APT data sets contain substantial noise. Given that sufficiently general predictive models for such noise remain elusive, crystallography tools for APT face several limitations: their robustness to noise is limited, and therefore so too is their capability to identify and distinguish different crystal structures and orientations. In addition, the tools are sequential and demand substantial manual interaction. In combination, this makes robust uncertainty quantification with automated high-throughput studies of the latent crystallographic information a difficult task with APT data. To improve the situation, the existing methods are reviewed and how they link to the methods currently used by the electron and X-ray diffraction communities is discussed. As a result of this, some of the APT methods are modified to yield more robust descriptors of the atomic arrangement. Also reported is how this enables the development of an open-source software tool for strong scaling and automated identification of a crystal structure, and the mapping of crystal orientation in nanocrystalline APT data sets with multiple phases.

scholarly journals PRISMA: A robust and intuitive tool for high-throughput processing of chemical spectra

2021 ◽  
Author(s):  
Eibar Flores ◽  
Nataliia Mozhzhukhina ◽  
Xinyu Li ◽  
Poul Norby ◽  
Aleksandar Matic ◽  
...  
Keyword(s):  
High Throughput ◽  
Functional Materials ◽  
Spectroscopic Technique ◽  
Energy Storage And Conversion ◽  
X Ray Diffraction ◽  
Graphite Composite ◽  
X Ray ◽  
Human In The Loop ◽  
Analysis Process ◽  
Diffraction Patterns

The popularization of high-throughput spectroscopies to characterize functional materials requires the simultaneous development of new analysis tools to efficiently process large numbers of measurements into scientifically meaningful observables. Here we introduce PRISMA, an open-source tool to rapidly analyze hundreds of spectra in a semi-automated way. PRISMA follows a human-in-the-loop workflow, where the user interacts with an intuitive graphical user interface (GUI) to control multiple steps in the spectrum analysis process: trimming, baseline correction, and peak fitting. The user tunes the analysis in real-time and applies the optimal parameters to all spectra, outputting processed results in an easy-to-read csv format within seconds. Crucially, the tuned parameters are stored to guarantee the full reproducibility of the analysis. We describe the functionalities implemented in PRISMA and test its capabilities with three experimental cases relevant to the study of electrochemical energy storage and conversion devices: temperature-dependent Raman measurement of phase transitions, a linear Raman mapping of a graphite composite electrode, and an operando X-ray diffraction experiment of LiNiO2 Li-ion electrode. Even if X-ray diffraction is not a spectroscopic technique, diffraction patterns are represented as one-dimensional arrays of counts equally suitable for analysis with PRISMA. The case studies demonstrate the robustness of the app and its ability to unearth insightful trends in peak parameters, which are easier to represent, interpret and further analyze with more advanced techniques.

scholarly journals PRISMA: A robust and intuitive tool for high-throughput processing of chemical spectra

2021 ◽  
Author(s):  
Eibar Flores ◽  
Nataliia Mozhzhukhina ◽  
Xinyu Li ◽  
Poul Norby ◽  
Aleksandar Matic ◽  
...  
Keyword(s):  
High Throughput ◽  
Functional Materials ◽  
Spectroscopic Technique ◽  
Energy Storage And Conversion ◽  
X Ray Diffraction ◽  
Graphite Composite ◽  
X Ray ◽  
Human In The Loop ◽  
Analysis Process ◽  
Diffraction Patterns

The popularization of high-throughput spectroscopies to characterize functional materials requires the simultaneous development of new analysis tools to efficiently process large numbers of measurements into scientifically meaningful observables. Here we introduce PRISMA, an open-source tool to rapidly analyze hundreds of spectra in a semi-automated way. PRISMA follows a human-in-the-loop workflow, where the user interacts with an intuitive graphical user interface (GUI) to control multiple steps in the spectrum analysis process: trimming, baseline correction, and peak fitting. The user tunes the analysis in real-time and applies the optimal parameters to all spectra, outputting processed results in an easy-to-read csv format within seconds. Crucially, the tuned parameters are stored to guarantee the full reproducibility of the analysis. We describe the functionalities implemented in PRISMA and test its capabilities with three experimental cases relevant to the study of electrochemical energy storage and conversion devices: temperature-dependent Raman measurement of phase transitions, a linear Raman mapping of a graphite composite electrode, and an operando X-ray diffraction experiment of LiNiO2 Li-ion electrode. Even if X-ray diffraction is not a spectroscopic technique, diffraction patterns are represented as one-dimensional arrays of counts equally suitable for analysis with PRISMA. The case studies demonstrate the robustness of the app and its ability to unearth insightful trends in peak parameters, which are easier to represent, interpret and further analyze with more advanced techniques.

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.

Examination of Rabbit Fc Crystals

1968 ◽  
Vol 26 ◽  
pp. 140-141
Author(s):  
J. P. Robinson ◽  
P. G. Lenhert
Keyword(s):  
Molecular Weight ◽  
Flat Plate ◽  
Phosphate Buffer ◽  
Asymmetric Unit ◽  
X Ray Diffraction ◽  
X Ray ◽  
Neutral Ph ◽  
Small Crystals ◽  
Carbon Coated ◽  
Diffraction Patterns

Crystallographic studies of rabbit Fc using X-ray diffraction patterns were recently reported. The unit cell constants were reported to be a = 69. 2 A°, b = 73. 1 A°, c = 60. 6 A°, B = 104° 30', space group P21, monoclinic, volume of asymmetric unit V = 148, 000 A°3. The molecular weight of the fragment was determined to be 55, 000 ± 2000 which is in agreement with earlier determinations by other methods.Fc crystals were formed in water or dilute phosphate buffer at neutral pH. The resulting crystal was a flat plate as previously described. Preparations of small crystals were negatively stained by mixing the suspension with equal volumes of 2% silicotungstate at neutral pH. A drop of the mixture was placed on a carbon coated grid and allowed to stand for a few minutes. The excess liquid was removed and the grid was immediately put in the microscope.

Control of the phase composition of advanced calcium phosphates using an x-ray diffractometer with a curved position-sensitive detector

2020 ◽  
Vol 86 (6) ◽  
pp. 29-35
Author(s):  
V. P. Sirotinkin ◽  
O. V. Baranov ◽  
A. Yu. Fedotov ◽  
S. M. Barinov
Keyword(s):  
Phase Composition ◽  
Calcium Phosphates ◽  
Position Sensitive Detector ◽  
Sensitive Detector ◽  
X Ray Diffraction ◽  
X Ray ◽  
Impurity Phases ◽  
Position Sensitive ◽  
Diffraction Peaks ◽  
Diffraction Patterns

The results of studying the phase composition of advanced calcium phosphates Ca10(PO4)6(OH)2, β-Ca3(PO4)2, α-Ca3(PO4)2, CaHPO4 · 2H2O, Ca8(HPO4)2(PO4)4 · 5H2O using an x-ray diffractometer with a curved position-sensitive detector are presented. Optimal experimental conditions (angular positions of the x-ray tube and detector, size of the slits, exposure time) were determined with allowance for possible formation of the impurity phases during synthesis. The construction features of diffractometers with a position-sensitive detector affecting the profile characteristics of x-ray diffraction peaks are considered. The composition for calibration of the diffractometer (a mixture of sodium acetate and yttrium oxide) was determined. Theoretical x-ray diffraction patterns for corresponding calcium phosphates are constructed on the basis of the literature data. These x-ray diffraction patterns were used to determine the phase composition of the advanced calcium phosphates. The features of advanced calcium phosphates, which should be taken into account during the phase analysis, are indicated. The powder of high-temperature form of tricalcium phosphate strongly adsorbs water from the environment. A strong texture is observed on the x-ray diffraction spectra of dicalcium phosphate dihydrate. A rather specific x-ray diffraction pattern of octacalcium phosphate pentahydrate revealed the only one strong peak at small angles. In all cases, significant deviations are observed for the recorded angular positions and relative intensity of the diffraction peaks. The results of the study of experimentally obtained mixtures of calcium phosphate are presented. It is shown that the graphic comparison of experimental x-ray diffraction spectra and pre-recorded spectra of the reference calcium phosphates and possible impurity phases is the most effective method. In this case, there is no need for calibration. When using this method, the total time for analysis of one sample is no more than 10 min.

Infrared spectroscopic study of the YPO4-YCrO4 system

1985 ◽  
Vol 50 (10) ◽  
pp. 2139-2145
Author(s):  
Alexander Muck ◽  
Eva Šantavá ◽  
Bohumil Hájek
Keyword(s):  
Spectroscopic Study ◽  
Infrared Spectra ◽  
Point Of View ◽  
Mixed Crystals ◽  
Crystal Symmetry ◽  
Infrared Spectroscopic Study ◽  
X Ray Diffraction ◽  
X Ray ◽  
Infrared Spectroscopic ◽  
Diffraction Patterns

The infrared spectra and powder X-ray diffraction patterns of polycrystalline YPO4-YCrO4 samples are studied from the point of view of their crystal symmetry. Mixed crystals of the D4h19 symmetry are formed over the region of 0-30 mol.% YPO4 in YCrO4. The Td → D2d → D2 or C2v(GS eff) correlation is appropriate for both PO43- and CrO43- anions.

scholarly journals Deep learning for visualization and novelty detection in large X-ray diffraction datasets

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Lars Banko ◽  
Phillip M. Maffettone ◽  
Dennis Naujoks ◽  
Daniel Olds ◽  
Alfred Ludwig
Keyword(s):  
Thin Film ◽  
Crystal Structure ◽  
Artificial Intelligence ◽  
Deep Learning ◽  
Novelty Detection ◽  
Structural Similarity ◽  
X Ray Diffraction ◽  
X Ray ◽  
Diffraction Patterns ◽  
Post Hoc

AbstractWe apply variational autoencoders (VAE) to X-ray diffraction (XRD) data analysis on both simulated and experimental thin-film data. We show that crystal structure representations learned by a VAE reveal latent information, such as the structural similarity of textured diffraction patterns. While other artificial intelligence (AI) agents are effective at classifying XRD data into known phases, a similarly conditioned VAE is uniquely effective at knowing what it doesn’t know: it can rapidly identify data outside the distribution it was trained on, such as novel phases and mixtures. These capabilities demonstrate that a VAE is a valuable AI agent for aiding materials discovery and understanding XRD measurements both ‘on-the-fly’ and during post hoc analysis.

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