Semi‐quantification of binary saline solutions by Raman spectroscopy: Implications for Europa
Autor: | Jose Antonio Manrique, Marco Veneranda, Yaiza Merino‐Lomas, Fernando Rull, Elena Charro, Manuel A. Gonzalez, Jose Manuel Lopez, Eduardo Rodríguez Gutiez, Jose Aurelio Sanz‐Arranz, Sylvestre Maurice, Guillermo Lopez‐Reyes |
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Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Journal of Chemometrics. |
ISSN: | 1099-128X 0886-9383 |
Popis: | Producción Científica The Europa lander is a concept for a potential future planetary exploration mission which purpose is to characterize the icy shell of Europa and to search for organics. To achieve this objective, the current concept of the lander includes a Raman spectrometer, such as RLS instrument, that could be able to analyze (sub) surface targets in their solid and liquid form. Knowing that ice and brines of Europa are potentially enriched by sulfate and chlorides, this work seeks to evaluate if Raman spectroscopy could be used to semi quantify the saline content of water solutions using space-like instrumentation. To do so, MgSO4 and MgCl2 were used to prepare three sets of water solutions. Raman analyses were then performed by the laboratory simulator of the ExoMars Raman Laser Spectrometer (RLS), which has been defined as the threshold system for the Europa Lander. After data analysis, two different semi-quantification approaches were tested, and their results compared. Although univariate calibration curves proved to successfully quantify the content of SO42− and Cl− anions dissolved in mono-analyte water solutions, this strategy provided very poor results when applied to binary saline mixtures. Overcoming this issue, the non-linearity prediction ability of Artificial Neural Networks (ANNs) in combination with bandfitting allows to successfully resolve the complexity of the vibrational perturbation suffered by the OH region, which is caused by the cross interaction of H2O molecules with different anions. Ministerio de Economía y Competitividad, Grant/Award Number: PID2019-107442RBC31. |
Databáze: | OpenAIRE |
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