Mass Spectrometry Laboratory, MolSys Research Unit, University of Liège, Liège, Belgium.
Early Life Traces & Evolution Laboratory, UR Astrobiology, University of Liège, Liège, Belgium.
Analyst. 2021 Nov 22;146(23):7306-7319. doi: 10.1039/d1an01514a.
The Mars 2020 and ExoMars 2022, rover-based missions are specifically dedicated to the search for evidence of life and will both utilise Raman spectrometers on the surface of Mars. Raman spectroscopy is indeed a valuable analytical technique for planetary exploration that enables characterisation of rocks and soils collected directly from the surface or retrieved as cores and subsequently crushed when extracted from the subsurface with a drill. On Mars, the miniaturised spectrometers will interrogate ancient geological deposits, in order to try and identify hydrated or aqueously altered minerals and organic matter to assess the habitability of Mars. While the identification of relevant hydrous minerals and organic components is the primary analytical objective of the missions, quantifying their abundances would be of particular significance for interpreting past geological conditions ( formation or alteration processes) and for ascertaining the putative presence of biosignatures. Therefore, we have developed quantitative models that enable the quantification of both mineral proportions from crushed mixtures of geological components and spiked mixtures containing organic analytes dispersed in mineral matrices. Based on data normalisation with appropriate standards (internal and external), we demonstrate that robust quantitative models can be (1) applied for solid dispersions of various complexities relevant to planetary exploration; and (2) applied to different Raman set-ups, including an instrument representative of the ExoMars Raman Laser Spectrometer. With important Raman-active minerals (calcite, gypsum, baryte, quartz), we demonstrate that using a correction factor , based on the ratio of apparent Raman scattering coefficients, the relative proportion of minerals in binary mixtures can be accurately determined. Regarding the organics, evaluated in clay-rich sediments (Fe-smectite) and crushed rocks of coarse-grained fraction (>100μm), we establish calibration curves in the concentration range 2-20 wt% for non-resonant compounds (L-cysteine, phthalic acid, adenine) and even lower (<1 wt%) for pre-resonant anthracene. Despite large levels of heterogeneity, the Raman analyses of these solid dispersions verify that quantitative Raman analyses can be performed in the context of robotic exploration studies.
“火星 2020 号”和“ExoMars 2022 号”火星车任务专门用于寻找生命迹象,这两项任务都将在火星表面使用拉曼光谱仪。拉曼光谱确实是一种用于行星探测的有价值的分析技术,可以对直接从表面采集的岩石和土壤或从地下钻取的岩芯进行特征描述,随后进行粉碎。在火星上,微型光谱仪将对古老的地质沉积物进行探测,以尝试识别水合或水蚀变矿物和有机物,从而评估火星的宜居性。虽然识别相关的含水矿物和有机成分是这些任务的主要分析目标,但定量它们的丰度对于解释过去的地质条件(形成或变化过程)以及确定可能存在的生物特征都具有特别重要的意义。因此,我们开发了定量模型,能够对粉碎的地质成分混合物和含有分散在矿物基质中的有机分析物的加标混合物中的矿物比例进行定量。通过使用适当的标准(内部和外部)进行数据归一化,我们证明了(1)可以将稳健的定量模型应用于与行星探测相关的各种复杂的固体分散体;(2)可以应用于不同的拉曼仪器设置,包括具有代表性的 ExoMars 拉曼激光光谱仪。对于重要的拉曼活性矿物(方解石、石膏、重晶石、石英),我们证明,使用基于表观拉曼散射系数比的校正因子,可以准确确定二元混合物中矿物的相对比例。对于在富含粘土的沉积物(铁蒙脱石)和粗粒级(>100μm)的粉碎岩石中评估的有机物,我们建立了在 2-20wt%浓度范围内的非共振化合物(L-半胱氨酸、邻苯二甲酸、腺嘌呤)和甚至更低(<1wt%)浓度范围内的预共振蒽的校准曲线。尽管存在很大的不均匀性,但这些固体分散体的拉曼分析证明了在机器人探测研究中可以进行定量拉曼分析。