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Data from: Visualizing mineralization processes and fossil anatomy using synchronous synchrotron X-ray fluorescence and X-ray diffraction mapping

Citation

Gueriau, Pierre et al. (2020), Data from: Visualizing mineralization processes and fossil anatomy using synchronous synchrotron X-ray fluorescence and X-ray diffraction mapping, Dryad, Dataset, https://doi.org/10.5061/dryad.s7h44j13z

Abstract

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.

Methods

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 mm2) 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 1a). 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:

(1) Synchrotron X-Ray Fluorescence elemental maps

Methods: 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 1b, logarithmic) grey or color scales that go from dark to light, respectively for low to high intensities.

Data: 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

(2) Synchrotron X-Ray Diffraction detector images

Methods: A few XPAD detector images are shown in the paper, either simply after flat correction (figure 1c) or after conversion to (2θ-Ѱ) coordinates (figure 2e). These images are represented using logarithmic color scales that go from dark to light, respectively for low to high intensities.

Data: figure1c_left_DATA_XRD.txt; figure1c_right_DATA_XRD.txt; figure2e_DATA_XRD.xlsx

(3) Diffractograms

Methods: XPAD detector images were processed (azimuthal data regrouping along y direction) to extract their respective diffractograms (Intensity vs. 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.

Data: figure1d_DATA_XRD.xlsx; figure2f_DATA_XRD.xlsx

(4) Synchrotron X-Ray Diffraction mineral maps

Methods: 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.

Data: 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

(5) Crystallite sizes

Methods: 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.

Data: 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

(6) Local texture measurements

Methods: 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 3f–h). 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 µm2 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.

Data: 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

Usage Notes

(1) Synchrotron X-Ray Fluorescence elemental maps

How to use: The .txt maps are text images that can be opened using the freeware ImageJ (>File >Import >Text image...).  The .tif RGB stacks can also be open using the freeware ImageJ, by simply dragging and dropping the file into ImageJ.

(2) Synchrotron X-Ray Diffraction detector images

How to use: The .txt files are text images that can be opened using the freeware ImageJ (>File >Import >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).

(3) Diffractograms

How to use: The .xlsx files gather Intensity vs. 2θ diffractograms that can be plotted within Excel.

(4) Synchrotron X-Ray Diffraction mineral maps

How to use: The .txt maps are text images that can be opened using the freeware ImageJ (>File >Import >Text image...).  The .tif RGB stacks can also be open using the freeware ImageJ, by simply dragging and dropping the file into ImageJ.

(5) Crystallite sizes

How to use: The .txt maps are text images that can be opened using the freeware ImageJ (>File >Import >Text image...).  The .tif RGB stack can also be open using the freeware ImageJ, by simply dragging and dropping the file into ImageJ.

(6) Local texture measurements

How to use: 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 (>File >Import >Text image...).

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Award: Finance Code 001 (Programa Nacional de Pós Doutor