A customizable software for fast reduction and analysis of large X-ray scattering data sets: applications of the new DPDAK package to small-angle X-ray scattering and grazing-incidence small-angle X-ray scattering

Abstract

X-ray scattering experiments at synchrotron sources are characterized by large and constantly increasing amounts of data. The great number of files generated during a synchrotron experiment is often a limiting factor in the analysis of the data, since appropriate software is rarely available to perform fast and tailored data processing. Furthermore, it is often necessary to perform online data reduction and analysis during the experiment in order to interactively optimize experimental design. This article presents an open-source software package developed to process large amounts of data from synchrotron scattering experiments. These data reduction processes involve calibration and correction of raw data, one- or two-dimensional integration, as well as fitting and further analysis of the data, including the extraction of certain parameters. The software, DPDAK (directly programmable data analysis kit), is based on a plug-in structure and allows individual extension in accordance with the requirements of the user. The article demonstrates the use of DPDAK for on- and offline analysis of scanning small-angle X-ray scattering (SAXS) data on biological samples and microfluidic systems, as well as for a comprehensive analysis of grazing-incidence SAXS data. In addition to a comparison with existing software packages, the structure of DPDAK and the possibilities and limitations are discussed.

Keywords: computer programs; data analysis; data reduction; grazing-incidence small-angle X-ray scattering; small-angle X-ray scattering.

Figure 1

(a) Work- and dataflow during a synchrotron experiment with online data analysis by DPDAK. Devices at the beamline produce a constant raw data flow. The raw data (detector images, motor positions) are read instantly by the DPDAK framework. Depending on the used plug-ins, a resulting data set of reduced data (curves, maps, scalar values etc.) is produced and stored in a database. The results can be accessed by the user via the GUI. (b) Screenshot of DPDAK during online analysis of SAXS on bone at the BESSY μSpot beamline (data presented in Fig. 2 ▶). The left side shows the user interface with file path, sequence and several evaluation parameters. The right side shows four plots representing details of the evaluation of the SAXS data: upper left is a radial integration, upper right the same data in a log–log plot, lower left shows a Porod plot and lower right a Kratky plot.

Figure 2

Results of processed SAXS data collected at the μSpot beamline, BESSY II, HZB. (a) Callus of a rat bone: SEM image (BSE) with T (color-coded circles) and ρ parameters (gray level of the triangles within the T circles), and predominant particle orientation (direction of gray triangles). (b) Azimuthal intensity distribution for determination of the ρ parameter. (c) Kratky plot for determination of the T parameter.

Figure 3

Example code for a plug-in calculating the sum, the average, the minimum and the maximum intensity of a rectangular region inside a detector image.

Figure 4

Results of processed SAXS data collected at ID 13, ESRF, with a micrometre sized beam. (a) Mouse bone: femur with an osteotomy, imaged with BSE. (b) T parameter map. (c) ρ parameter map.

Figure 5

(a) Five representative GISAXS patterns from thin (left) to thick (right) Au layers. The gray dashed line indicates the q_y position of the Yoneda peak of silicon. (b) Map of extracted horizontal line cuts at the Yoneda peak position of silicon as a function of the frame number. The inset shows an individual fit of frame 2000, indicated by the white (data) and red (fit) dashed lines. (c) Map of the corresponding fitted horizontal line cuts. The logarithmic intensity scale bar applies to all figures.

Figure 6

(a) Peak position (black) and FWHM (red) for frames 250–3150 from Fig. 5 ▶(c). The dashed lines indicate several kinetic transition points between different growth stages (I–IV). (b) Intensity at the corresponding exit angles α_c of Au (green) and Si (blue).

Figure 7

(a) Mapping of the horizontal line cuts (q_y) collected from 0.1 s time-resolved two-dimensional GISAXS data. Intensity peaks related to the polymer template (I) and metal clusters (II) are indicated. (b) q_y values of the position of peak (I) and peak (II) as a function of effective metal load layer thickness δ, extracted via fitting of individual line cuts. The inset shows an individual fit of frame 3000 as obtained by the DPDAK software.

Figure 8

The flow of wormlike polymeric micelles can be studied using SAXS by scanning the microfluidic channel with a microfocused X-ray beam. (a) The measured SAXS patterns reveal micelles in parallel, tilted, transitional and perpendicular orientations depending on their location, as indicated by the straight lines. (b) The information from these SAXS patterns is used to generate color maps in real time using DPDAK. Each of these pixels is color coded on the basis of the averaged ROI of the parallel or the perpendicular micelle orientation. (c) The SAXS results are also in good agreement with the corresponding polarization microscopic images that are based on the samples birefringence. Here, the blue color represents a parallel micelle orientation with respect to the flow, while the orange color indicates a perpendicular orientation.