Chemical imaging with a spaceflight LDMS instrument for planetary exploration

One of the analytical advantages of Laser desorption/ablation mass spectrometry (LDMS) is its potential for spatially-resolved composition analysis of solid samples, supporting 2D chemical mapping and/or 3D depth profiling as ions are generated within a focused laser beam footprint. In this study, we present the imaging capabilities of a spaceflight LDMS instrument named CORALS (Characterization of Ocean Residues and Life Signatures), centered around an Orbitrap™ mass analyzer ruggedized for planetary missions. Four types of samples with distinct morphologies and compositions were characterized, specifically high-purity metal foils, organic fingerprint impressions, Widmanstätten patterns in the Gibeon iron meteorite, and multiple mixtures of gypsum and hematite with different volumetric proportions. We show that the CORALS instrument supports a wide field-of-view (FOV: ∼1.4 × 1.7 mm 2 ) with fine spatial resolution (∼100 μm), along with the demonstration to analyze organic patterns on a 100-μm scale pattern and to perform semi-quantitative analysis to distinguish two different phases. These capabilities will enable elemental, molecular, and isotopic analysis of morphologies and textures in planetary samples ranging from sub-mm to mm scales (e.g., biochemical structures such as stromatolite layers, mineralogical diversity of rocks and soils, and co-located organics and host minerals). This study confirms that CORALS is a high-value instrument that complements previous spaceflight chemical imaging instruments (e.g., SHERLOC on NASA’s perseverance rover), providing critical context for detailed in-situ analysis of potential biosignatures. • Chemical imaging capability of a spaceflight LDMS instrument is experimentally shown. • The wide FOV (∼1.4 × 1.7 mm 2 ) and fine spatial resolution (∼100 μm) was confirmed. • Characteristic structures of organics and inorganics were successfully imaged. • Volume fraction of two minerals within the FOV could be identified <10% error.