Laser-induced breakdown spectroscopy (LIBS) is a valuable tool for evaluating the geochemical characteristics of Martian rocks and was applied in the Tianwen-1 Mars exploration mission with the payload called Mars Surface Composition Detection Package (MarSCoDe). In this work, we developed a laboratory standoff LIBS system combined with a Martian simulation chamber to examine the geochemical characteristics of igneous rocks, with the intention to provide a reference and a basis for the analysis of LIBS data acquired by MarSCoDe. Fifteen igneous geological standards are selected for a preliminary LIBS spectroscopic study. Three multivariate analysis methods were applied to characterize the geochemical features of igneous standards. First, quantitative analysis was done with Partial Least Squares (PLS) and Least Absolute Shrinkage and Selection (LASSO), where the major element compositions of these samples (SiO₂, Al₂O₃, T Fe₂O₃, MgO, CaO, K₂O, Na₂O, and TiO₂) were derived. The predicted concentrations ((Fe₂O₃ + MgO)/SiO₂, Fe₂O₃/MgO, Al₂O₃/SiO₂, and (Na₂O + K₂O)/Al₂O₃) were used to identify the geochemical characteristics of igneous rocks. Also, PCA, an unsupervised multivariate method was tested to directly identify the igneous rock lithology with no prior quantification. Higher correlation (0.82–0.88) are obtained using Principal Component Analysis (PCA) scores than using predicted elemental ratios derived by PLS and LASSO, indicating that PCA is better suited to identify igneous rock lithology than via quantitative concentrations. This preliminary study, using this LIBS system, provides suitable methods for the elemental prediction and geochemical identification of martian rocks, and we will use extended geologic standards and continue to build a robust LIBS spectral library for MarSCoDe based on this LIBS system in the future.

China’s first Mars exploration mission, named Tianwen-1, landed on Mars on 15 May 2021. The Mars Surface Composition Detector (MarSCoDe) payload onboard the Zhurong rover applied the laser-induced breakdown spectroscopy (LIBS) technique to acquire chemical compositions of Martian rocks and soils. The quantitative interpretation of MarSCoDe-LIBS spectra needs to establish a LIBS spectral database that requires plenty of terrestrial geological standards. In this work, we selected 316 terrestrial standards including igneous rocks, sedimentary rocks, metamorphic rocks, and ores, whose chemical compositions, rock types, and chemical weathering characteristics were comparable to those of Martian materials from previous orbital and in situ detections. These rocks were crushed, ground, and sieved into powders less than <38 μm and pressed into pellets to minimize heterogeneity at the scale of laser spot. The chemical compositions of these standards were independently measured by X-ray fluorescence (XRF). Subsequently, the LIBS spectra of MAL standards were acquired using an established LIBS system at Shandong University (SDU-LIBS). In order to evaluate the performance of these standards in LIBS spectral interpretation, we established multivariate models using partial least squares (PLS) and least absolute shrinkage and selection (LASSO) algorithms to predict the abundance of major elements based on SDU-LIBS spectra. The root mean squared error (RMSE) values of these models are comparable to those of the published models for MarSCoDe, ChemCam, and SuperCam, suggesting these PLS and LASSO models work well. From our research, we can conclude that these 316 MAL targets are good candidates to acquire geochemistry information based on the LIBS technique. These targets could be regarded as geological standards to build a LIBS database using a prototype of MarSCoDe in the near future, which is critical to obtain accurate chemical compositions of Martian rocks and soils based on MarSCoDe-LIBS spectral data.

With the development of technology and methodologies, Raman spectrometers are becoming efficient candidate payloads for planetary materials characterizations in deep space exploration missions. The National Aeronautics and Space Administration (NASA) already deployed two Raman instruments, Super Cam and SHERLOC, onboard the Perseverance Rover in the Mars 2020 mission. In the ground test, the SHERLOC team found an axial offset (~720 μm) between the ACI (Autofocus Context Imager) and the spectrometer focus, which would obviously affect the acquired Raman intensity if not corrected. To eliminate this error and, more importantly, simplify the application of Raman instruments in deep space exploration missions, we propose an automatic focusing method wherein Raman signals are optimized during spectrum collection. We put forward a novel method that is realized by evaluating focus conditions numerically and searching for the extremum point as the final focal point. To verify the effectiveness of this method, we developed an Auto-focus Raman Probe (SDU-ARP) in our laboratory. This method provides a research direction for scenarios in which spectrometers cannot focus on a target using any other criterion. The utilization of this auto-focusing method can offer better spectra and fewer acquisitions in focusing procedure, and the spectrometer payload can be deployed in light-weight bodies (e.g., asteroids) or in poor illumination conditions (e.g., the permanently shadowed region in the Lunar south polar area) in deep space exploration missions.