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Quantitative Raman calibration of sulfate-bearing polymineralic mixtures: a S quantification in sedimentary rocks on Mars

Published online by Cambridge University Press:  14 September 2018

Chloé Larre*
Affiliation:
Université de Nantes, Faculté des Sciences et Techniques, Laboratoire de Planétologie et Géodynamique (LPG), UMR CNRS 6112, 2 rue de la Houssinière, 44322 Nantes, France
Yann Morizet
Affiliation:
Université de Nantes, Faculté des Sciences et Techniques, Laboratoire de Planétologie et Géodynamique (LPG), UMR CNRS 6112, 2 rue de la Houssinière, 44322 Nantes, France
Catherine Guillot-Deudon
Affiliation:
Université de Nantes, Faculté des Sciences et Techniques, Laboratoire de Planétologie et Géodynamique (LPG), UMR CNRS 6112, 2 rue de la Houssinière, 44322 Nantes, France IMN, Institut des Matériaux Jean Rouxel de Nantes, UMR CNRS 6502, 2 rue de la Houssinière, 44322 Nantes, France
Fabien Baron
Affiliation:
Université de Nantes, Faculté des Sciences et Techniques, Laboratoire de Planétologie et Géodynamique (LPG), UMR CNRS 6112, 2 rue de la Houssinière, 44322 Nantes, France
Nicolas Mangold
Affiliation:
Université de Nantes, Faculté des Sciences et Techniques, Laboratoire de Planétologie et Géodynamique (LPG), UMR CNRS 6112, 2 rue de la Houssinière, 44322 Nantes, France
*
*Author for correspondence: Chloé Larre, Email: chloe.larre@univ-nantes.fr
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Abstract

The NASA 2020 Mars mission is a Curiosity-type rover whose objective is to improve the knowledge of the geological and climatic evolution of Mars and to collect rock samples for return to Earth. The new rover has a payload of seven instruments including the SuperCam instrument which consists of four tools including a Raman spectrometer. This Raman device will be non-destructive and will analyse the surface remotely in order to determine the mineralogy of rocks and, by extent, to detect and quantify major elements such as sulfur. Sulfur has been detected as sulfate (Ca,Mg,Fe-sulfates) in sedimentary rocks. This element is difficult to quantify using the laser ablation tool of the ChemCam instrument on-board the Curiosity rover.

We propose a Raman calibration to constrain the sulfur abundance in polymineralic mixtures. We acquired Raman signatures on binary and ternary mechanical mixtures containing Ca and Mg sulfates, mixed with natural silicate minerals supposed to be relevant to basaltic-sedimentary rocks at the surface of Mars: olivine, clinopyroxene, orthopyroxene and plagioclase. Using the Voigt function to process the Raman spectra from samples extracted from our mixtures allows us to calculate the initial proportions of our preparations of Ca and Mg sulfates. From these simulations, calibration equations have been provided allowing us to determine sulfate proportions (CaSO4 and MgSO4) in a mixture with basaltic minerals. With the presented calibration, S can be quantified at a lower limit of 0.7 wt.% in Martian soil.

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Article
Copyright
Copyright © Mineralogical Society of Great Britain and Ireland 2018 
Figure 0

Table 1. Origins and compositions of basaltic minerals (olivine, pyroxenes and plagioclase, determined by scanning electron microscopy analysis) and sulfates used in this investigation.

Figure 1

Fig. 1. (a) Pellet of a 90/10 mixture of olivine (weight fraction WFolivine = 0.90) and gypsum (WFgypsum = 0.10) named GOLI90; (b) 5 mm mapping of spectrum intensities acquired by Raman spectroscopy showing the homogeneity of GOLI90; and (c) the average spectrum issued from the 5 mm mapping of GOLI90 with ν1 peaks (symmetric stretching mode of SiO4 and SO4 molecules) of olivine and gypsum reported.

Figure 2

Fig. 2. Polymineralic Raman spectra of pure samples with acquisition time for (a) olivine; (b) Mg-sulfate; (c) gypsum; (d) plagioclase; (e) clinopyroxene; and (f) orthopyroxene. Significant peaks for each mineral are shown. For peak assignments see Table 2.

Figure 3

Table 2. Specific peak assignments for each mineral used in this study*.

Figure 4

Table 3. Samples prepared in this study for binary and ternary mixtures with sulfates (Ca and Mg) and basaltic minerals (i.e olivine, orthopyroxene, clinopyroxene and plagioclase). For each mixture the simulated peak is given, followed by the resulting calibration equation.*

Figure 5

Fig. 3. Global spectra for every mixture of olivine with gypsum in different proportions: (a) WFolivine = 0.99; (b) WFolivine = 0.95; (c) WFolivine = 0.90; and (d) WFolivine = 0.80; with their main peaks reported. Variations of gypsum ν1 (symmetric stretch of SO4) peak intensity are shown as red arrows. Magnified (890–1100 cm−1 area) spectra acquired by Raman spectroscopy after mapping, from different mixtures of olivine with gypsum in several proportions: (e) WFgypsum = 0.01; (f) WFgypsum = 0.05; (g) WFgypsum = 0.10; and (h) WFgypsum = 0.20. Spectra are correlated with peak simulations: blue for olivine and green for gypsum. Red curves are cumulative peaks and black dotted lines are residuals from simulations. Weight fractions are calculated with peak simulations and reported in boxes in each graph and in Table 3.

Figure 6

Fig. 4. Calibration coefficients calculated from simulated areas of gypsum and mineral mixes versus the theoretical weight fraction (WF) of gypsum. Black squares are simulated samples with their relative errors. Red lines correspond to calibration lines extrapolated from calibration coefficients depending on the theoretical weight fraction of gypsum. Calibration lines established on four binary mixtures of: (a) plagioclase; (b) orthopyroxene; (c) clinopyroxene; and (d) olivine; with gypsum in different proportions (WFgypsum = 0.20, 0.10, 0.05, 0.03, 0.01). Equations and linear regression coefficient (R2) of each calibration line are reported in boxes in each graph.

Figure 7

Fig. 5. Calibration line for ternary mixtures of gypsum (WFgypsum = 0.2, 0.1, 0.05) with olivine (WFolivine = 0.40, 0.50, 0.50) and clinopyroxene (WFclinopyroxene = 0.40, 0.40, 0.45). Black squares are simulation results with errors (black vertical lines). Red line is the calibration line calculated from simulation results. Equation and regression linear coefficient (R2) are specified in the graph box.

Figure 8

Fig. 6. Calibration coefficients calculated from simulated areas of Mg-sulfate and mineral mixes versus the theoretical weight fraction (WF) of the sulfate. Black squares are simulated samples with their relative errors. Red lines correspond to calibration lines extrapolated from calibration coefficients depending on theoretical weight fraction of Mg-sulfate. Calibration lines established on four binary mixtures of: (a) orthopyroxene; (b) plagioclase; (c) clinopyroxene; and (d) olivine; with Mg-sulfate in different proportions (WFgypsum = 0.20, 0.10, 0.05 and 0.03). Equations and linear regression coefficients (R2) of each calibration lines are reported in boxes for every graph.

Figure 9

Fig. 7. Weight fractions calculated for sulfates (Ca- and Mg-sulfate) depending on its theoretical weight fraction in each mixture of olivine, clinopyroxene, orthopyroxene and plagioclase. Black = gypsum binary samples; blue = Mg-sulfate mixtures; red diamonds = ternary mixtures of gypsum.

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