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electronic reprint
Journal of
AppliedCrystallography
ISSN 0021-8898
Editor: Gernot Kostorz
XRD2DScan: new software for polycrystalline materialscharacterization using two-dimensional X-ray diffraction
Alejandro B. Rodriguez-Navarro
Copyright © International Union of Crystallography
Author(s) of this paper may load this reprint on their own web site provided that this cover page is retained. Republication of this article or itsstorage in electronic databases or the like is not permitted without prior permission in writing from the IUCr.
J. Appl. Cryst. (2006). 39, 905–909 Rodriguez-Navarro � XRD2DScan
computer programs
J. Appl. Cryst. (2006). 39, 905–909 doi:10.1107/S0021889806042488 905
Journal of
AppliedCrystallography
ISSN 0021-8898
Received 11 July 2006
Accepted 13 October 2006
# 2006 International Union of Crystallography
Printed in Great Britain – all rights reserved
XRD2DScan: new software for polycrystallinematerials characterization using two-dimensionalX-ray diffraction
Alejandro B. Rodriguez-Navarro
Departamento de Mineralogıa y Petrologıa, Universidad de Granada, 18002 Granada, Spain. Correspondence
e-mail: anava@ugr.es
XRD2DScan is a Windows application for displaying and analyzing two-
dimensional X-ray diffraction patterns collected with an area detector. This
software allows users to take full advantage of diffractometers that are equipped
with an area detector but that cannot readily process the information contained
in diffraction patterns from polycrystalline materials. XRD2DScan has many
capabilities for generating different types of scans (2� scan, scan, d spacing
versus angle), which allows users to extract the maximum amount of
information from two-dimensional patterns. Analyses of multiple data files can
be fully automated using batch processing. The use of the software is illustrated
through several examples.
1. Introduction
X-ray area detectors [e.g. multi-wire proportional counters, charge-
coupled devices (CCDs) and image-plate systems] were initially used
for protein crystallography in the 1980s. More recently, their use has
extended to small-molecule structural analyses and powder diffrac-
tometry (Sulyanov et al., 1994; Hammersley et al., 1996; He, 2003;
Blanton, 2006). This technology is particularly advantageous for the
characterization of polycrystalline materials because it allows for the
simultaneous collection of many orders of Bragg reflections. In
addition to the enormous reduction of data acquisition time for
analyses, two-dimensional diffraction patterns contain much more
information than conventional linear scans (i.e. �–2� scans) collected
using standard powder diffractometers (Hirsch & Kellar, 1952; Klug
& Alexander, 1974; Bunge et al., 2002; Ischia et al., 2005). Two-
dimensional diffraction patterns of polycrystalline samples typically
consist of concentric (Debye–Scherrer) rings produced by the
superposition of reflections from many crystals illuminated by the
X-ray beam, which are oriented with a set of (hkl ) crystallographic
planes oriented to fulfil the Bragg condition (Cullity, 1977).
Depending on sample characteristics, these rings might be continuous
or spotty and display specific variation in the intensities along them.
These features contain important information about the micro-
structure of the sample: grain size, preferential orientation, mosaicity,
stress etc. Additionally, two-dimensional patterns can be converted
into conventional linear scans by radial or azimuthal integration of
pixel intensities. The generated linear scans can be processed as usual
for mineral phase identification, crystallinity or Rietveld refinement
studies. Nevertheless, during this data reduction procedure, most of
the information regarding the microstructure of the material is lost.
To take full advantage of two-dimensional diffraction for poly-
crystalline materials characterization, specialized software is
required, capable of extracting the information contained in two-
dimensional diffraction patterns (Hammersley et al., 1996). Here we
introduce XRD2DScan: new software specially designed for
displaying and analyzing two-dimensional diffraction patterns of
polycrystalline samples collected using area detectors. This software
is especially useful for users having access to single-crystal diffract-
ometers equipped with an area detector but lacking software for
analyzing powder diffraction patterns. Basic features of this software
are described and illustrated in different example applications.
2. Software description and use
XRD2DScan is a Windows application, developed using Borland
Delphi, that displays and processes the information contained in two-
dimensional diffraction patterns (or frames). The typical interface of
the program is shown in Fig. 1. The software supports Bruker, Oxford
Diffraction, ADSC and Mar Research data file formats from 512 �512 up to 2048 � 2048 pixels in size, although other formats can be
implemented upon request. Once the software loads the data file
containing pixel intensities, the two-dimensional diffraction pattern
and the calculated 2� scan are displayed (Fig. 1). The user can then
select a 2� and angular range within the two-dimensional pattern
using MaskSector (from the software main menu) to process the data
further. Hereafter, the most useful analytical tools of the software are
described.
2.1. ThetaScanSector
This menu option calculates and displays the 2� scan generated
using pixels within a angular range defined using MaskSector. This
scan is calculated by radially integrating pixel intensities. Basically,
the software finds pixels within the selected range for every 2� step
and integrates their intensities. The 2� step size defines the resolution
of the 2� scan, which can be set automatically or by the user. To be
able to compare these data with the data collected using a standard
powder diffractometer, with a point detector, the intensity for every
2� step is averaged by the number of pixels contributing to it.
Otherwise, the intensities will increase with the 2� angle or with the
perimeter of the Debye rings. This is equivalent to a normalization by
a factor 1/R, where R is the radius (in pixels) of a ring.
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2.2. PsiScanSector
This tool calculates and displays the scan for a given 2� angular
range. More specifically, it displays the intensity profile along a Debye
ring as a function of angle. This scan is calculated by azimuthal
integration of pixel intensities falling within a ring defined by a 2�range (selected using MaskSector) for every step. The step size
defines the resolution of the scan, which can be set by the user.
2.3. Background subtraction
The background of the intensity profile in the 2� scan or � scan is
removed using a ball algorithm. Basically, an elliptical ball is defined
by an angular width (which needs to be at least the peak width) and
an intensity height. This ball scans the bottom of the intensity profile
and calculates the background profile as the highest point reached by
the ball. The width and height of the ball can be defined interactively
by the user. During background subtraction, the software calculates
the integrated intensity of the background and that of all peaks. This
information is useful for determining the percentage of crystalline
versus amorphous phases (Klug & Alexander, 1974).
2.4. FindPeaks
This tool searches for peaks along the intensity profile of a 2� or scan and calculates the position, maximum (and integrated) intensity
and angular width of each peak found. Results are reported as a peak
list in a text file: the Logbook.
2.5. Batch processing of data files
A very useful and important feature of this software is that it is
capable of analyzing data files without user intervention. Batch
processing is convenient for analyzing many data files. Depending on
the information needed, the user can select among different options
of the batch-processing tool. For instance, this tool can automatically
calculate and save to a file the 2� scan, remove the background,
search for peaks and report the information (peak intensity, area and
width) of all peaks found. It can do the same for scans and d-
spacing plots.
2.6. Logbook
The software has a logbook in a notepad-style text file which keeps
a record of the user actions and all information processed by the
software.
2.7. FindCenter tool
Setting a correct pattern center is one of the most critical steps for
processing the data of two-dimensional diffraction patterns. A correct
center would produce the sharpest peaks in the linear patterns.
Setting a center can be carried out with or without user intervention
using different implemented methodologies. (i) Manual: the user can
set the center coordinates. (ii) Fully automatic: the program finds the
pattern center automatically just by a click of a button. (iii) The
program finds the center of gravity of the two-dimensional pattern.
(iv) Center of a Debye ring: the program can automatically search for
the center of a Debye ring in the frame (i.e. defined by a 2� angular
range). (v) Center of an ellipse: the user marks points circumscribing
an ellipse (i.e. in a Debye ring) with the mouse and the program
calculates its center. Methods (ii) and (iv) give the best results and
sharpest peaks. Note that the center-of-gravity method is only useful
if the 2� angle of the detector is set to zero. All other methods work at
detector 2� angles different from zero.
computer programs
906 Rodriguez-Navarro � XRD2DScan J. Appl. Cryst. (2006). 39, 905–909
Figure 1Main window of the XRD2DScan software, displaying a two-dimensional and 2� diffraction pattern of a polycrystalline sample. The blue lines define the selected angularsector for intensity integration set using MaskSector. At the top right corner is a window with the experimental setup for the analysis. At the bottom right corner is aLogbook, recording the user actions and information processed by the software.
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2.8. Correction of 2h angles
If the positions of peaks in the 2� scan are shifted from the theo-
retical values (a fairly common problem), it is possible to correct for
the angular offset by shifting the 2� values by a constant value or by
adjusting the sample-to-detector distance or detector size. For the
latter procedures, the software calculates the sample-to-detector
distance or detector size that matches the theoretical and measured
peak positions and uses this value to calculate a corrected 2� scan.
2.9. IntegrateSector
This tool integrates the intensity of all pixels within the angular
sector defined by MaskSector and reports the result in the Logbook.
Integration of sectors could be useful for measuring individual
reflection spots and for estimating the relative amount of crystalline
versus amorphous phases.
2.10. d spacing in a sector
The program calculates and displays the values of the interplanar
distance, d (in A), as a function of angle for a given Debye ring. The
Debye ring is selected by the user, defining a 2� angular range using
the MaskSector tool. The d spacing is calculated by dividing the two-
dimensional pattern into 72 sectors of 5� (of angle) and finding the
2� angle having the maximum peak intensity in each sector. The d
values are calculated from these 2� angles as �/[2sin(2�/2)]. This
option is useful for studying residual stresses in materials (Klug &
Alexander, 1974).
2.11. Integration of sector slices
The intensity of all pixels within the 2� angular range defined by
MaskSector is integrated in slices of angular width defined by the
user. The result is reported in the Logbook and saved to an output file
(experiment.slc). Integration of sector slices could be useful for
determining pole figures from two-dimensional diffraction patterns
(Ischia et al., 2005).
2.12. Mathematical operations with frames
It is possible to perform several mathematical operations using the
Math menu, which can be useful for the analysis of two-dimensional
patterns. The basic operations implemented by the software are as
follows. (i) AddFrames: add to the present two-dimensional pattern
the intensity of one or more selected data files. This is useful for
integrating the information contained in several patterns into a single
pattern to simulate, for example, long exposures or rotation photo-
graphs, or to minimize the effect of preferential orientation. (ii)
SubtractFrames: subtract from the present two-dimensional pattern
the intensity of another file. This can be used, for instance, to remove
the background intensity or the contribution of air scattering. (iii)
MultiplybyConstant: this option allows the user to multiply the
intensity of each pixel by a constant, for instance, to rescale the
pattern. (iv) AddConstant: this option allows the addition of a
constant value to the intensity of each pixel.
3. Application examples
3.1. Mineral phase identification
Fig. 2(a) displays the two-dimensional diffraction pattern of a piece
of an archaeological iron artifact. This sample was measured by
reflection using a single-crystal diffractometer equipped with a CCD
detector (SMART APEX, Bruker, Germany) and the experimental
conditions defined in Table 1. This pattern consists of rings displaying
two distinct characteristics. Some rings are formed by isolated
reflection spots and others are continuous. Spotty rings are produced
by a coarse-grained mineral phase, while continuous rings are
produced by a fine-grained mineral phase. The broad band around 8�
corresponds to embedding resin.
Fig. 2(b) shows the 2� scan calculated using the full angular range
measured by the detector (2� from 0 to 45� and from 0 to 360�).
Fig. 2(c) shows this scan after removing the background and
searching for peaks. Bragg peaks found are marked by a blue open
circle. The integrated range defined by the software for each peak is
shown in blue. Two mineral phases, pearlite (native iron) and
magnetite, corresponding, respectively, to the coarse and fine mineral
computer programs
J. Appl. Cryst. (2006). 39, 905–909 Rodriguez-Navarro � XRD2DScan 907
Figure 2(a) Two-dimensional diffraction pattern of a piece of an archeological iron artifactdisplaying two distinct types of Debye rings (some spotty and some continuous).Each ring type is associated with a different mineral phase. (b) Calculated 2� scanusing all pixels (full angular range). (c) 2� scan (after background subtraction)displaying peaks found by the software (marked as blue circles). Each peak isassigned to one of the three mineral phases identified [native iron (solid square),magnetite (arrow) and geothite (open square)].
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phases, were identified by comparing the d spacings of peaks with
those reported in PDF files for common iron minerals. An additional
small peak was identified as goethite, a probable minority phase.
Table 2 reports the peak list and information found by the software.
Table 2 also shows peak assignments to the different mineral phases
identified. Note that pearlite produced narrower peaks than
magnetite, owing to the higher crystallinity of the former phase.
However, two-dimensional diffraction patterns enable the differ-
entiation of mineral phases, based on their different microstructural
characteristics, more easily than conventional linear scans.
3.2. Crystal size quantification
Fig. 3(b) displays the variation of intensity along a Debye–Scherrer
ring associated with a 220 reflection as a function of angle for
different SiC abrasive powders with average sizes of 9, 7 and 5 mm. scans were calculated by integrating pixel intensities within the 2�range, from 26.229 to 26.939�, selected in the two-dimensional pattern
shown in Fig. 3(a). Intensity profiles consist of a series of peaks of
similar intensities. Each peak within a ring corresponds to the
reflection of an individual crystal oriented with their (220) planes in
diffraction condition. Peak intensities increase on average as crystal
size increases, while the number of peaks decreases. For crystal sizes
of 3 mm or smaller, under chosen experimental conditions, the rings
are continuous and their intensity profile does not show any
systematic variation with angle, so no peaks can be measured. From
the intensity of the reflection spots, and using a calibration curve such
as the one depicted in the inset of Fig. 3(b), crystal size can be
determined. Note also that crystal sizes from different mineral phases
present in a sample can be determined independently by measuring
peak intensities in rings associated with their characteristic reflec-
tions. This methodology is described in detail elsewhere (Rodriguez-
Navarro et al., 2006).
3.3. Preferential orientation quantification
Two-dimensional diffraction patterns are very informative
regarding the orientation of crystals within a sample. Preferential
orientation of crystals causes some rings to disappear and/or only a
small fraction of them to be displayed. Because certain crystal-
lographic planes or directions are aligned, their associated reflecting
spots group into a fraction of a Debye ring or arc (Klug & Alexander,
1974). The stronger the orientation, the smaller would be the length
of the ring sector. Conversely, a randomly oriented sample would
display all and complete rings. Fig. 4(a) shows the two-dimensional
diffraction pattern of the inner surface of a mollusk shell (Ostrea
edulis) measured by reflection using the experimental conditions
defined in Table 1. This pattern indicates that the calcite crystals in
the shell are preferentially oriented with their c axis perpendicular to
the shell surface and rotated around it [(001) fiber texture]. More
detailed information about crystal orientation can be deduced by
analyzing the intensity profile along a Debye ring sector as a function
computer programs
908 Rodriguez-Navarro � XRD2DScan J. Appl. Cryst. (2006). 39, 905–909
Table 1Conditions for diffraction experiments.
Diffractometer D8 Bruker, GermanyDetector SMART APEX CCDRadiation Mo K�Acceleration voltage 50 kVFilament current 30 mACollimator diameter 0.5 mmCollimator length 170 mmExposure time 20 sDistance to detector 60 mm
Figure 3(a) Two-dimensional diffraction pattern of an SiC abrasive powder of 9 mm, showing slightly spotty rings. (b) scans along a Debye–Scherrer ring associated with the 220reflection of SiC samples with different crystal sizes. The intensity profiles displayed correspond to samples with average crystal sizes of 9, 7 and 5 mm. As the size of thecrystal decreases, the peak intensities decrease, while the number of peaks increases. The inset displays a cross-plot of the average peak intensities as a function of crystal size,showing a strong positive correlation between these two variables (R2 = 0.9983). These samples were measured by transmission using the experimental conditions reported inTable 1 and an exposure time of 120 s.
Table 2List of peaks found in the 2� scan of the archeological iron sample and theircorrespondence to mineral phases.
Peak 2� (�) d (A) Intensity (counts) Area (counts) Width (�) Mineral
1 9.750 4.182 28 156 0.418 Goethite2 11.475 3.555 40 155 0.291 Pearlite3 14.700 2.778 109 453 0.312 Pearlite4 16.200 2.522 98 901 0.690 Magnetite5 19.425 2.106 39 187 0.360 Magnetite6 20.925 1.957 56 251 0.336 Pearlite7 23.850 1.720 77 541 0.527 Magnetite8 25.275 1.624 22 123 0.419 Magnetite9 27.600 1.490 44 295 0.503 Magnetite10 29.175 1.411 27 102 0.283 Pearlite11 42.675 0.977 22 86 0.293 Pearlite
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of angle. For instance, Fig. 4(b) shows the intensity profile of a scan for the 006 reflection of calcite in the selected angular range of
the two-dimensional pattern shown in Fig. 4(a). The full width at half-
maximum (FWHM) of this broad peak or band is 18.3�, indicating
that crystals have their c axes quite well aligned. Thus, the angular
spread of this band indicates the scattering crystal orientations and is
a measurement of the degree of crystal alignment along specific
crystallographic directions (in this case the c axis) (Checa et al., 2005).
4. Conclusions
Area detectors record the X-ray intensity distribution of two-
dimensional diffraction patterns which can be later processed and
analyzed using adequate software to extract the maximum amount
of information. Such software allows the use of a single-crystal
diffractometer equipped with an area detector as a sophisticated
powder diffractometer. These diffractometers are very expensive
(typically over 300 000 euros) and it is worth giving them another use.
The basic features and use of the XRD2DScan software have been
described here as applied to polycrystalline materials characteriza-
tion. It is also demonstrated through specific examples that a wealth
of information regarding sample mineral phases and microstructural
characteristics can be extracted very quickly and easily from the two-
dimensional diffraction pattern using this software.
5. Software availability and system requirements
XRD2DScan software (installation program and user manual) can be
downloaded from http://www.ugr.es/~anava/xrd2dscan.htm or can be
obtained by contacting the author. The software can be installed on
Windows 98, 2000 and XP operating systems. A display resolution of
1280 � 800 pixels and an up-to-date computer are recommended.
This study was funded through grant REN2003-07375 and
Programa Ramon y Cajal (from the Spanish Government) and
Research Group RNM 179 (Junta de Andalucia). The author is
indebted to Concepcion Lopez Moratalla for helping with mathe-
matical calculations. The author also thanks Dr Daniel Martin Ramos
(UGR) and Daniel Chateigner (Universite de Caen Basse, France)
for useful comments.
References
Blanton, T. N. (2006). Powder Diffr. 21, 91–96.Bunge, H. J., Wcislak, L., Klein, H., Garbe, U. & Schneider, J. R. (2002). Adv.
Eng. Mater. 4, 300–305.Checa, A. G., Rodrıguez-Navarro, A. B. & Esteban-Delgado, F. J. (2005).
Biomaterials, 26, 6404–6414.Cullity, B. D. (1977). Elements of X-ray Diffraction. New York: Addison-
Wesley.Hammersley, A. P., Svensson, S. O., Hanfland, M., Fitch, A. N. & Hausermann,
D. (1996). High Pressure Res. 14, 235–248.He, B. B. P. (2003). Powder Diffr. 18, 71–85.Hirsch, P. B. & Kellar, J. N. (1952). Acta Cryst. 5, 162–167.Ischia, G., Wenk, H.-R., Lutterotti, L. & Berberich, F. (2005). J. Appl. Cryst. 38,
377–380.Klug, H. P. & Alexander, L. E. (1974). X-ray Diffraction Procedures for
Polycrystalline and Amorphous Materials. New York: John Wiley.Rodriguez-Navarro, A. B., Alvarez-Lloret, P., Ortega-Huertas, M. &
Rodriguez-Gallego, M. (2006). J. Am. Ceram. Soc. 89, 2232–2238.Sulyanov, S. N., Popov, A. N. & Kheiker, D. M. (1994). J. Appl. Cryst. 27, 934–
947.
computer programs
J. Appl. Cryst. (2006). 39, 905–909 Rodriguez-Navarro � XRD2DScan 909
Figure 4(a) Two-dimensional diffraction pattern of the inner surface of a mollusk shell displaying a strong preferential orientation. The angular sector selected (2� from 28.0 to 29.2�
and from 120.0 to 230.0�) is delimited by blue lines. (b) Intensity profile of the scan, for the 006 reflection of calcite, calculated using pixels in the selected angular sector.The angular width of the band is 18.3�.
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