The Raman Laser Spectrometer for the ExoMars Rover Mission to Mars

Rull, Fernando; Maurice, S.; Hutchinson, Ian; Moral, Andoni; Pérez, Carlos Barceló; Díaz, Carlos; Colombo, M.; Belenguer, T.; López‐Reyes, Guillermo; Sansano, A.; Forni, O.; Parot, Yann; Striebig, Nicolas; Woodward, S.; Howe, C.; Tarcea, N.; Rodríguez, P.; Seoane, Laura; Santiago, A.; Rodríguez-Prieto, José A.; Medina, Jesús; Gallego, P.; Canchal, R.; Santamaría, P.; Ramos, G.; Vago, Jorge L.; Team, on behalf of the RLS

doi:10.1089/ast.2016.1567

Cited by 215 publications

(216 citation statements)

References 43 publications

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“…In this study, this is achieved by applying Raman spectroscopy under various temperature and pressure conditions and in vacuum. Furthermore, it is important to anticipate resulting Raman spectra with respect to space missions like ExoMars2020 (ESA) or Mars 2020 (NASA) that have a Raman spectrometer on board and to preevaluate the data in order to optimize the instrument design during its development to ensure correct interpretation.…”

Section: Introductionmentioning

confidence: 99%

Raman spectra of hydrous minerals investigated under various environmental conditions in preparation for planetary space missions

Weber

Böttger²,

Pavlov³

et al. 2018

J Raman Spectroscopy

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Raman spectrometers will be part of the scientific payload of the future lander missions to Mars, icy moons, and asteroids. Their primary task is the search for life including the detailed characterization of the planetary environment. H2O/OH−‐bearing minerals are essential for biological processes; thus, their investigation will have a special focus. Cyclic temperature variations on planetary surfaces, for example, on Mars between 300 and 140 K from summer midday to winter night, induce re‐organization of the internal mineral structures, which can be monitored by Raman spectroscopy. Therefore, temperature dependent changes in Raman spectra under step‐wise cooling/re‐heating of typical planetary surface related H2O/OH−‐bearing minerals (e.g., carnallite, natrolite, gypsum, phlogopite, talc, and tremolite) are the focus of this work. Spectra were taken under space relevant simulated conditions, from vacuum and cryogenic temperature to room conditions, including those that resemble the Martian surface atmosphere. Special attention was dedicated to the typical vibrational stretching modes of H2O/OH−‐bearing minerals. H2O‐bearing minerals exhibit significantly different temperature related changes when compared to OH−‐bearing minerals. We observed the formation of an ice‐like Raman spectrum during step‐wise deep cooling of carnallite. Gypsum shows a blue shift of the H2O band with decreasing temperature. All other investigated minerals display no significant variations over the entire Raman relevant spectral range. The results of this study are be made available in a Raman database of the flight Raman instruments.

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Section: Introductionmentioning

confidence: 99%

Raman spectra of hydrous minerals investigated under various environmental conditions in preparation for planetary space missions

Weber

Böttger²,

Pavlov³

et al. 2018

J Raman Spectroscopy

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“…[8] A Raman laser spectrometer (RLS) is part of the science instrument payload of the European Space Agency 2018 ExoMars mission; the RLS instrument will target mineralogical and astrobiological investigations on the surface and subsurface of Mars. [9,10] Raman will also be used on the upcoming NASA Mars 2020 mission as part of the SuperCam and SHERLOC instruments. [11] What all these applications have in common is their dependence on software and mineralogical databases for phase identification and quantification of relative abundances of mineral components.…”

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confidence: 99%

Machine learning tools formineral recognition and classification from Raman spectroscopy

Carey

Boucher

Mahadevan

et al. 2015

J Raman Spectroscopy

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Tools for mineral identification based on Raman spectroscopy fall into two groups: those that are largely based on fits to diagnostic peaks associated with specific phases, and those that use the entire spectral range for multivariate analyses. In this project, we apply machine learning techniques to improve mineral identification using the latter group. We test the effects of common spectrum preprocessing steps, such as intensity normalization, smoothing, and squashing, and found that the last is superior. Next, we demonstrate that full-spectrum matching algorithms exhibit excellent performance in classification tasks, without requiring time-intensive dimensionality reduction or model training. This class of algorithms supports both vector and trajectory input formats, exploiting all available spectral information. By combining these insights, we find that optimal mineral spectrum matching performance can be achieved using careful preprocessing and a weighted-neighbors classifier based on a vector similarity metric. IntroductionUse of Raman spectroscopy in the geosciences is growing rapidly, as evidenced by burgeoning publications in the fields of geology, cultural anthropology, environmental science, and, in particular, planetary science. Raman spectrometers have been proposed for exploration of a diverse range of extraterrestrial targets including asteroids, [1] Europa, [2,3] Mars, [4][5][6] the Moon, [7] and Venus. [8] A Raman laser spectrometer (RLS) is part of the science instrument payload of the European Space Agency 2018 ExoMars mission; the RLS instrument will target mineralogical and astrobiological investigations on the surface and subsurface of Mars. [9,10] Raman will also be used on the upcoming NASA Mars 2020 mission as part of the SuperCam and SHERLOC instruments. [11] What all these applications have in common is their dependence on software and mineralogical databases for phase identification and quantification of relative abundances of mineral components. Because of the structural diversity and chemical complexity of naturally occurring minerals, optimal applications for these purposes require an infusion of work into development of appropriate software and mineral databases.In practice, users commonly depend on a combination of matching software distributed by spectrometer manufacturers and one-on-one comparisons with database spectra for their identifications, but these types of identification have two critical limitations. First, identifications are only as good as the databases used to match them. No database can be entirely comprehensive, so it cannot be unequivocally claimed that any spectrum is a 'perfect match' to exactly one other phase.The RRUFF database was founded in 2006 at Arizona State University by Robert Downs to remedy this situation by providing coverage of all known mineral species. [12] It has quickly become the preeminent resource available for Raman spectra of minerals. RRUFF currently contains over 20 378 spectra acquired at several different laser wavelengths from orien...

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“…Our spectra also show that at micron scales, sedimentary material like this has a high degree of spatial variability, though the extent to which this is a problem is dependent on the spot size of the Raman instrument. The spot size of our instrument (1–4 μm) is far lower than those of the planned ExoMars (50 μm) and Mars 2020 (<100 μm for SHERLOC and ~1 mm for SuperCam) instruments (Abbey et al, ; Rull et al, ; Wiens et al, ), which will therefore be less effected by micron‐scale variability, but also not as able to identify small features, including sedimentary‐scale grain variation. The ability to separate identifying peaks is also dependent on the spectral resolution of the instrument.…”

Section: Discussionmentioning

confidence: 80%

Y‐Mars: An Astrobiological Analogue of Martian Mudstone

Stevens

Steer

McDonald

et al. 2018

Earth and Space Science

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NASA's Mars Science Laboratory mission has collected evidence of a long‐lasting habitable environment in the Sheepbed sediments of Gale Crater on Mars. The geochemistry of this mudstone suggests that the lake filling the crater in Mars' past had a neutral pH and low salinity and contained elements and redox couples required by life. We produced a geochemical analogue to the Sheepbed mudstone by mixing a collection of its primary minerals to match the X‐Ray diffraction data from Mars Science Laboratory. Here we describe the production of the Y‐Mars (Yellowknife‐Mars) analogue and characterize its properties, including the presence of background carbon, nitrogen, and sulfur. We highlight some of the unavoidable issues involved in making analogues, especially for astrobiological applications. The Y‐Mars analogue has a number of applications for astrobiological research, but more analogues are required to properly represent the diversity of Martian sedimentary contexts.

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The Raman Laser Spectrometer for the ExoMars Rover Mission to Mars

Cited by 215 publications

References 43 publications

Raman spectra of hydrous minerals investigated under various environmental conditions in preparation for planetary space missions

Raman spectra of hydrous minerals investigated under various environmental conditions in preparation for planetary space missions

Machine learning tools formineral recognition and classification from Raman spectroscopy

Y‐Mars: An Astrobiological Analogue of Martian Mudstone

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