HOW TO ANALYZE SYNCHROTRON DATA
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1 HOW TO ANALYZE SYNCHROTRON DATA 1
2 SYNCHROTRON APPLICATIONS - WHAT Diffraction data are collected on diffractometer lines at the world s synchrotron sources. Most synchrotrons have one or more user facilities or ports that perform powder diffraction experiments. The extreme X-ray photon flux rate of a synchrotron allows users much latitude to vary instrumental conditions. Diffractometer lines often use custom optics and detectors designed to improve resolution, sensitivity or capture data quickly. 2
3 SYNCHROTRON APPLICATIONS - WHY Materials can be studied dynamically while under stress, strain, heating or cooling. The high flux rate allows users to rapidly collect many data scans as a function of conditions. High resolution combined with high signal to noise provides improved accuracy in structure solution, phase identification and quantitative analysis. 3
4 SYNCHROTRON APPLICATIONS - HOW To best use the PDF databases for synchrotron applications, users need to adjust applicable parameters in the database. This includes: 1) Using integrated intensity options for all entries. 2) Changing the input wavelength for all data simulations. 3) Adjusting both the optical geometry and peak width for simulations. 4) Using calculated patterns where possible. Calculated patterns have intensities calculated from , experimental patterns have intensities from ) Adjusting background and peak finding algorithms in SIeve for higher sensitivity. (Note: The enhanced signal to noise in most synchrotron experiments means that low intensity peaks are often observed.) 4
5 Synchrotron Help Preferences In PDF-4+ Release 2012 versions and later, a new button was added to the preferences setting, Set Synchrotron Defaults. This changes the wavelength, instrumental peak profiles, and step width for all database calculations and simulations. The profiles were determined from instrumental standards used at the Argonne National Light Source. A default wavelength of Å, was used, but the user can put in any input wavelength. Typical polarization and specimen thicknesses were also input. 5
6 COMPARISON OF EXPERIMENTAL (PD3) AND SIMULATED DATA FOR LAB6 (USING Å AND SYNCHROTRON DEFAULTS ) Large Range in Observed Intensity 6
7 SYNCHROTRON DATA VERSUS LABORATORY DATA Wavelengths are variable. Incident beam is often monochromatic and/or parallel. Peak resolution is high for crystalline materials (i.e., very small instrumental contributions to the peak profiles, 0.01 FWHM or less). High count rates and signal to noise ratio are expected for synchrotron data. 7
8 SYNCHROTRON DATA Peaks below 0.3% relative intensity Clearly resolved low intensity peaks and high signal to noise. 8
9 CHANGING DISPLAY OPTIONS USING SIEVE+ In previous slides, it was shown that display options in PDF-4+ can be customized using preferences, which is this icon shown in many of the display screens in PDF-4+. 9
10 CUSTOM DISPLAYS IMPORTING DATA Import data using the drop down Menu s. The importer supports GSAS formats. This selection will display a browser to find data files. Select Other for wavelength, input wavelength of Å used here. 10
11 After the user inputs the experimental wavelength, a dialog box appears that guides the user through a series of data processing steps. The first step is the removal of background using a Sonneveld-Visser algorithm. The background is highlighted by the blue line. This experiment used a glass capillary as a specimen holder and the background shown arises from incoherent scattering from the capillary glass. Depending on the specimen size and capillary wall thickness in relation to the beam size, sometimes the capillary scatter will be easily observed and other times will not. DATA PROCESSING 11
12 Peak Finding Peak finding uses a second derivative algorithm. Due to the exceptionally good signal to noise ratio in synchrotron data, it is usually best to set the derivative and intensity detection limits to very low numbers. It is also helpful to use the mouse to drag and magnify the plot so that minor peaks can be identified. In this multiphase specimen, 355 peaks were found and some were still not identified and had to be chosen by manual methods. This is a point and click option at the bottom of the page. Manual selection option 12
13 Identification Data are imported into SIeve+ and can be viewed as either a d,i listing or as a complete diffraction pattern. In the example on the right, the pattern is shown in the bottom right panel. The d-spacing matches are shown in the top panel and sorted by the score based on comparing the experiment and reference. The bottom left panel shows the selected identification, D- glucose hydrate, its I/Ic scaling factor and contribution to the total diffraction intensity. Candidates can be viewed and compared to the experimental data by pointing and clicking on the candidates in the top panel and viewing the match in the bottom right panel. 13
14 Multi-phase Identification At any time, the user can choose to view a multiphase comparison by using a right click of the mouse on the previously shown (slide 13) screen in SIeve+. Selection of Open Simulated Profile with Experimental Data will produce a comparison of selected phases with the candidate phases in a single plot. The use of synchrotron defaults as shown in slide 5 will produce a plot with appropriate peak profiles for synchrotron data. In this comparison, the raw data in a vitamin pill is compared to vitamin C, glucose hydrate, iron fumarate and vitamin B. 14
15 SUMMED PHASES Patterns can be summed for the scaled components. There are options within the software to override the scaling, vary the profiles and the colors and ranges in the display. In this analysis, the four highest concentration phases were used in the simulation. This specimen also contains many low concentration phases that could be further identified and plotted. 15
16 CENTRUM PERFORMANCE 8 PHASE SOLUTION Red = Experimental data Black = 8 phase simulation of components The characteristics of this pattern are dominated by KCl and CaHPO4 dihydrate. Six additional minor phases have been identified. 16
17 SUMMARY New features have been added to the PDF-4+ database and associated software SIeve+ specific to synchrotron analyses. An option in the preferences module of PDF-4+ automatically changes several instrument settings to those found in global synchrotron facilities. Instrument profile settings can be user customized, the preference module saves time and convenience when processing synchrotron diffraction data sets. Dynamic memory has been reallocated within the product to allow larger data sets (typical of synchrotron data), to be quickly processed for rapid identification. Q and d-spacing plotting options have been added to Release 2013 Products. 17
18 MORE INFORMATION For more information on how to perform complex multi-phase simulations, see the pattern simulations tutorial. For more information on how to identify minor phases (below 10 wt %), see the tutorial and publication on Data Mining Trace Phase Analysis. For more information on synchrotron instrument functions as used in simulations and Rietveld refinements see the following: J. A. Kaduk and J. Reid, (2011), Typical values of Rietveld instrument profile Coefficients Powder Diffraction / Volume 26 / Issue 01 / March 2011, pp Copyright Cambridge University Press 2011 DOI: Published online: 05 March 2012 Note: Several authors have now reported identification of phases in concentrations below 0.3 wt % using synchrotron data. Significantly lower detection limits are possible with optimized (signal/noise) experiments. 18
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