DOI: 10.5061/dryad.s7h44j13z
title: Data from: Visualizing mineralization processes and fossil anatomy using synchronous synchrotron X-ray fluorescence and X-ray diffraction mapping

description: Fossils, including those that occasionally preserve decay-prone
 soft-tissues, are mostly made of minerals. Accessing their chemical
 composition provides unique insight into their past biology and/or the
 mechanisms by which they preserve, leading to a series of developments in
 chemical and elemental imaging. However, the mineral composition of
 fossils, particularly where soft-tissues are preserved, is often only
 inferred indirectly from elemental data, while X-ray diffraction that
 specifically provides phase identification received little attention.
 Here, we show the use of synchrotron radiation to generate not only X-ray
 fluorescence elemental maps of a fossil, but also mineralogical maps in
 transmission geometry using a two-dimensional area detector placed behind
 the fossil. This innovative approach was applied to millimetre-thick
 cross-sections prepared through three-dimensionally preserved fossils, as
 well as to compressed fossils. It identifies and maps mineral phases and
 their distribution at the microscale over centimetre-sized areas,
 benefitting from the elemental information collected synchronously, and
 further informs on texture (preferential orientation), crystallites size
 and local strain. Probing such crystallographic information is
 instrumental in defining mineralization sequences, reconstructing the
 fossilization environment and constraining preservation biases. Similarly,
 this approach could potentially provide new knowledge on other
 (bio)mineralization processes in environmental sciences. We also
 illustrate that mineralogical contrasts between fossil tissues and/or the
 encasing sedimentary matrix can be used to visualize hidden anatomies in
 fossils.
description: Data were collected at the DiffAbs beamline of the SOLEIL
 Synchrotron source (France). Synchronous synchrotron rapid scanning X-ray
 fluorescence and diffraction mapping (SRS-XRFD) was performed using an
 incident X-ray beam of 16.2 or 18 keV, monochromatised using a Si(111)
 double-crystal monochromator, with a beam size diameter reduced down to 50
 or 100 µm using platinum pinholes, or focused down to ~10 µm using
 Kirkpatrick-Baez mirrors. XRF was collected using a 4-element silicon
 drift detector (SDD, Vortex ME4, Hitachi High-Technologies Science
 America, Inc., total active area: 170 mm<sup>2</sup>) oriented
 at 90° to the incident beam, in the horizontal plane. XRD was collected in
 transmission geometry using a 2D hybrid pixel detector (XPAD S140, 240×560
 pixels of 130 µm each), placed behind the sample at a distance of
 typically 200–300 mm such to intercept diffraction rings over an angular
 range of ~7° in scattering angle (2θ). Two-dimensional scanning was done
 by moving laterally the fossils in a plane rotated around the vertical
 axis by 20° to the primary beam (i.e., incident angle), to limit X-ray
 beam footprint on the sample but also such that the sample exhibits its
 surface to the SDD detector (no shadowing of the reflected XRD signal,
 figure 1<i>a</i>). Mapping over the entire fossils at a 35–100
 µm lateral resolution was performed on the fly using the FLYSCAN platform.
 A full XRF spectrum and one or several XRD images were collected at each
 pixel. The present dataset
 includes 6 types of data: <strong><em>(1)
 Synchrotron X-Ray Fluorescence elemental
 maps</em></strong>
 <em>Methods:</em> All elemental
 distributions presented in the paper correspond to integrated intensities
 around emission lines of elements of interest (XRF peaks), represented
 using linear (expect figure 1<i>b</i>, logarithmic) grey or
 color scales that go from dark to light, respectively for low to high
 intensities.
 <em>Data:</em>
 figure1b_AsPb-map_DATA_XRF.txt; figure1b_Mn-map_DATA_XRF.txt;
 figure1b_Zn-map_DATA_XRF.txt; figure1b_stackRGB_DATA_XRF.tif;
 figure2b_Ca-map_DATA_XRF.txt; figure2b_Fe-map_DATA_XRF.txt;
 figure2b_Y-map_DATA_XRF.txt; figure2b_stackRGB_DATA_XRF.tif;
 figure5f_Y-map_DATA_XRF.txt <strong><em>(2)
 Synchrotron X-Ray Diffraction detector
 images</em></strong>
 <em>Methods:</em> A few XPAD
 detector images are shown in the paper, either simply after flat
 correction (figure 1<em>c</em>) or after conversion to (2θ-Ѱ)
 coordinates (figure 2<em>e</em>). These images are represented
 using logarithmic color scales that go from dark to light, respectively
 for low to high intensities.
 <em>Data:</em>
 figure1c_left_DATA_XRD.txt; figure1c_right_DATA_XRD.txt;
 figure2e_DATA_XRD.xlsx <strong><em>(3)
 Diffractograms</em></strong>
 <em>Methods:</em> XPAD detector
 images were processed (azimuthal data regrouping along y direction) to
 extract their respective diffractograms (Intensity <i>vs.</i>
 2θ profiles). Phase identification and 2θ calibration were performed using
 powder XRD diffractograms obtained on fragments of the sedimentary matrix
 (and of the fossil when possible) using the Match! software (Crystal
 Impact) making use of the International Centre for Diffraction Data
 (ICDD)- PDF 2015 database. Additional peaks in the XRD maps could then be
 identified using Match/ICDD database, as well as from the elemental
 information provided by the XRF data.
 <em>Data:</em>
 figure1d_DATA_XRD.xlsx; figure2f_DATA_XRD.xlsx
 <strong><em>(4) Synchrotron X-Ray Diffraction mineral
 maps</em></strong>
 <em>Methods:</em> During XPAD
 detector images processing 4D datasets (x, y, 2θ, intensity) were also
 generated, and then particular XRD contrast maps. Phase identification and
 2θ calibration is discussed above. All phase distributions presented in
 the paper correspond to integrated intensities of XRD peaks of interest,
 represented using linear grey or color scales that go from dark to light,
 respectively for low to high intensities.
 <em>Data:</em>
 figure1e_left_DATA_XRD.txt; figure1e_center_DATA_XRD.txt;
 figure1e_right_DATA_XRD.txt; figure2c_A211-map_DATA_XRD.txt;
 figure2c_C006-map_DATA_XRD.txt; figure2c_Q101-map_DATA_XRD.txt;
 figure2c_stackRGB_DATA_XRD.tif; figure2d_C012-map_DATA_XRD.txt;
 figure2d_C113-map_DATA_XRD.txt; figure2d_C202-map_DATA_XRD.txt;
 figure2d_stackRGB_DATA_XRD.tif; figure4a_17p97-map_DATA_XRD.txt;
 figure4a_25p09-map_DATA_XRD.txt; figure4a_26p01-map_DATA_XRD.txt;
 figure4a_stackRGB_DATA_XRD.tif; figure4b_22p51-map_DATA_XRD.txt;
 figure4b_26p97-map_DATA_XRD.txt; figure4b_27p63-map_DATA_XRD.txt;
 figure4b_stackRGB_DATA_XRD.tif; figure5b_FAp002-map-head_DATA_XRD.txt;
 figure5b_FAp211-map-head_DATA_XRD.txt;
 figure5b_phyll-map-head_DATA_XRD.txt; figure5b_stackRGB-head_DATA_XRD.tif;
 figure5b_FAp002-map-tail_DATA_XRD.txt;
 figure5b_FAp211-map-tail_DATA_XRD.txt;
 figure5b_phyll-map-tail_DATA_XRD.txt; figure5b_stackRGB-tail_DATA_XRD.tif;
 figure5c_FAp002-map-cropped_DATA_XRD.txt;
 figure5e_FAp002-map_DATA_XRD.txt
 <strong><em>(5) Crystallite
 sizes</em></strong>
 <em>Methods:</em> By Gaussian
 fitting the 2θ profile of XRD peaks attributed to different crystalline
 phases, corresponding crystallite sizes were extracted (for each pixel of
 the maps) by converting their full width at half maximum (FWHM) using
 Scherrer’s formula. It was assumed that only the crystallite size is
 contributing to the broadening, and an instrument resolution function
 measured as ~0.035° (amounting several 10 %, and up to 50 % of the
 measured peak FWHM) was also taken into account for FWHM deconvolution.
 Crystallite size distributions are represented in the paper using linear
 color scales that go from dark to light, respectively for low to high
 intensities.
 <em>Data:</em>
 figure2g_A211-crystSize-map_DATA_XRD.txt;
 figure2g_C006-crystSize-map_DATA_XRD.txt;
 figure2g_Q101-crystSize-map_DATA_XRD:txt;
 figure2g_stackRGB_DATA_XRD.tif
 <strong><em>(6)
 </em></strong><b><i>Local texture
 measurements</i></b> <em>Methods:</em> In order to confirm some microstructure results obtained using the local probe XRD approach, supplementary local texture measurements were performed. This was done by scanning it in azimuth (Φ, rotation around the sample surface normal) and elevation (Ѱ, rotation around the projection of the impinging X-ray beam on the sample surface), while recording, at each position, the X-ray scattered signal. The resulting intensity is represented in a map, in polar coordinates (azimuth angle and elevation, e.g. figures 3<i>f–h</i>). In this way, when one or several crystallites are oriented such that the Bragg law is fulfilled for the particular inter-reticular distance probed (or the particular Bragg angle 2θ), high signal is found in the particular corresponding regions of the polar map, allowing: i) to retrieve the particular orientation of the grains (j, y), and ii) to possibly quantify the volume ratio of that particular orientation, compared to other orientations on the map. Rapid texture measurements were performed using the XPAD area detector. The sample was illuminated by the impinging X-ray beam (of size ~ 150 × 150 µm<sup>2</sup> in this case) and the azimuth (Φ) and elevation (Ѱ) angles were scanned, the first one continuously. An image was recorded in each point, then texture maps for various 2θ angles (i.e. volumes) were reconstructed. Then, a similar dataset was recorded at the next vertical position on the sample. Local texture measurements are represented in the paper using logarithmic color scales that go from dark to light, respectively for low to high intensities. <em>Data:</em> Figure3b-d_DATA_XRD.xlsx; figure3f_left_DATA_XRD.txt; figure3f_right_DATA_XRD.txt; figure3g_left_DATA_XRD.txt; figure3g_right_DATA_XRD.txt; figure3h_left_DATA_XRD.txt; figure3h_right_DATA_XRD.txt
description: <strong><em>(1) Synchrotron X-Ray Fluorescence
 elemental maps</em></strong>
 <em>How to use:</em> The .txt maps
 are text images that can be opened using the freeware ImageJ (&gt;File
 &gt;Import &gt;Text image...).  The .tif RGB stacks can also be
 open using the freeware ImageJ, by simply dragging and dropping the file
 into ImageJ. <strong><em>(2) Synchrotron
 X-Ray Diffraction detector images</em></strong>
 <em>How to use:</em> The .txt
 files are text images that can be opened using the freeware ImageJ
 (&gt;File &gt;Import &gt;Text image...).  The .xlsx file
 gathers XYZ data (2θ-Ѱ-intensity) that can be exported as .txt and opened
 using ImageJ XYZ2DEM Importer plugin
 (https://imagej.nih.gov/ij/plugins/xyz2dem-importer.html).
 <strong><em>(3)
 Diffractograms</em></strong>
 <em>How to use:</em> The .xlsx
 files gather Intensity <i>vs.</i> 2θ diffractograms that can
 be plotted within Excel. 
 <strong><em>(4) Synchrotron X-Ray Diffraction mineral
 maps</em></strong> <em>How
 to use:</em> The .txt maps are text images that can be
 opened using the freeware ImageJ (&gt;File &gt;Import &gt;Text
 image...).  The .tif RGB stacks can also be open using the freeware
 ImageJ, by simply dragging and dropping the file into ImageJ.
 <strong><em>(5) Crystallite
 sizes</em></strong> <em>How
 to use:</em> The .txt maps are text images that can be
 opened using the freeware ImageJ (&gt;File &gt;Import &gt;Text
 image...).  The .tif RGB stack can also be open using the freeware ImageJ,
 by simply dragging and dropping the file into ImageJ.
 <strong><em>(6)
 </em></strong><b><i>Local texture
 measurements</i></b> <em>How
 to use:</em> The .xlsx file gathers XYZ data
 (2θ-z-intensity) that can be exported as .txt and open using ImageJ
 XYZ2DEM Importer plugin
 (https://imagej.nih.gov/ij/plugins/xyz2dem-importer.html). The .txt files
 are text images that can be opened using the freeware ImageJ (&gt;File
 &gt;Import &gt;Text image...).