International audienceChemCam is a remote sensing instrument suite on board the "Curiosity" rover (NASA) that uses Laser-Induced Breakdown Spectroscopy (LIBS) to provide the elemental composition of soils and rocks at the surface of Mars from a distance of 1.3 to 7 m, and a telescopic imager to return high resolution context and micro-images at distances greater than 1.16 m. We describe five analytical capabilities: rock classification, quantitative composition, depth profiling, context imaging, and passive spectroscopy. They serve as a toolbox to address most of the science questions at Gale crater. ChemCam consists of a Mast-Unit (laser, telescope, camera, and electronics) and a Body-Unit (spectrometers, digital processing unit, and optical demultiplexer), which are connected by an optical fiber and an electrical interface. We then report on the development, integration, and testing of the Mast-Unit, and summarize some key characteristics of ChemCam. This confirmed that nominal or better than nominal performances were achieved for critical parameters, in particular power density (>1 GW/cm2). The analysis spot diameter varies from 350 μm at 2 m to 550 μm at 7 m distance. For remote imaging, the camera field of view is 20 mrad for 1024×1024 pixels. Field tests demonstrated that the resolution (˜90 μrad) made it possible to identify laser shots on a wide variety of images. This is sufficient for visualizing laser shot pits and textures of rocks and soils. An auto-exposure capability optimizes the dynamical range of the images. Dedicated hardware and software focus the telescope, with precision that is appropriate for the LIBS and imaging depths-of-field. The light emitted by the plasma is collected and sent to the Body-Unit via a 6 m optical fiber. The companion to this paper (Wiens et al. this issue) reports on the development of the Body-Unit, on the analysis of the emitted light, and on the good match between instrument performance and science specifications

International audienceThe ChemCam instrument, which provides insight into martian soil chemistry at the submillimeter scale, identified two principal soil types along the Curiosity rover traverse: a fine-grained mafic type and a locally derived, coarse-grained felsic type. The mafic soil component is representative of widespread martian soils and is similar in composition to the martian dust. It possesses a ubiquitous hydrogen signature in ChemCam spectra, corresponding to the hydration of the amorphous phases found in the soil by the CheMin instrument. This hydration likely accounts for an important fraction of the global hydration of the surface seen by previous orbital measurements. ChemCam analyses did not reveal any significant exchange of water vapor between the regolith and the atmosphere. These observations provide constraints on the nature of the amorphous phases and their hydration

At Gale crater, Mars, ChemCam acquired its first laser-induced breakdown spectroscopy (LIBS) target on Sol 13 of the landed portion of the mission (a Sol is a Mars day). Up to Sol 800, more than 188 000 LIBS spectra were acquired on more than 5800 points distributed over about 650 individual targets. We present a comprehensive review of ChemCam scientific accomplishments during that period, together with a focus on the lessons learned from the first use of LIBS in space. For data processing, we describe new tools that had to be developed to account for the uniqueness of Mars data. With regard to chemistry, we present a summary of the composition range measured on Mars for major-element oxides (SiO 2 , TiO 2 , Al 2 O 3 , FeO T , MgO, CaO, Na 2 O, K 2 O) based on various multivariate models, with associated precisions.ChemCam also observed H, and the non-metallic elements C, O, P, and S, which are usually difficult to quantify with LIBS. F and Cl are observed through their molecular lines. We discuss the most relevant LIBS lines for detection of minor and trace elements (Li, Rb, Sr, Ba, Cr, Mn, Ni, and Zn). These results were obtained thanks to comprehensive ground reference datasets, which are set to mimic the expected mineralogy and chemistry on Mars. With regard to the first use of LIBS in space, we analyze and quantify, often for the first time, each of the advantages of using stand-off LIBS in space: no sample preparation, analysis within its petrological context, dust removal, sub-millimeter scale investigation, multi-point analysis, the ability to carry out statistical surveys and whole-rock analyses, and rapid data acquisition.We conclude with a discussion of ChemCam performance to survey the geochemistry of Mars, and its valuable support of decisions about selecting where and whether to make observations with more time and resource-intensive tools in the rover's instrument suite. In the end, we present a bird's-eye view of Cite this:

Laser-induced breakdown spectroscopy (LIBS) has been applied to the analysis of three chromium-doped soils. Two chemometric techniques, principal components analysis (PCA) and neural networks analysis (NNA), were used to discriminate the soils on the basis of their LIBS spectra. An excellent rate of correct classification was achieved and a better ability of neural networks to cope with real-world, noisy spectra was demonstrated. Neural networks were then used for measuring chromium concentration in one of the soils. We performed a detailed optimization of the inputs of the network so as to improve its predictive performances and we studied the effect of the presence of matrix-specific information in the inputs examined. Finally the inputs of the network--the spectral intensities--were replaced by the line areas. This provided the best results with a prediction accuracy and precision of about 5% in the determination of chromium concentration and a significant reduction of the data, too.

Laser-induced breakdown spectroscopy is used to measure chromium concentration in soil samples. A comparison is carried out between the calibration curve method and two chemometrics techniques: partial least-squares regression and neural networks. The three quantitative techniques are evaluated in terms of prediction accuracy, prediction precision, and limit of detection. The influence of several parameters specific to each method is studied in detail, as well as the effect of different pretreatments of the spectra. Neural networks are shown to correctly model nonlinear effects due to self-absorption in the plasma and to provide the best results. Subsequently, principal components analysis is used for classifying spectra from two different soils. Then simultaneous prediction of chromium concentration in the two matrixes is successfully performed through partial least-squares regression and neural networks.

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The ChemCam instrument that will equip the Mars Science Laboratory (MSL) rover uses laserinduced breakdown spectroscopy (LIBS) to remotely identify Martian rocks in the proximity of the rover, and to quantitatively assess their composition. Sample identification is then the first step of the chemical analysis, as a decision aid for monitoring the rover and/or before a subsequent composition measurement. In this paper we analyze our experimental spectra obtained in the laboratory by three chemometric methods-principal components analysis (PCA), soft independent modeling of class analogy (SIMCA) and partial least-squares discriminant analysis (PLS-DA)-to investigate the feasibility of rocks classification by remote LIBS. If PCA is very interesting for data visualization, SIMCA and PLS-DA enable the making of automatic predictions. We show that SIMCA is less sensitive than PLS-DA, but also more robust when it encounters spectra of an unknown rock. The instrument accuracy during MSL operations will benefit from a combination of the two approaches.

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