Search

Introduction. Oxia Planum is the selected landing site of the ExoMars mission [1]. A drilling system is installed on the ExoMars rover, able to analyze down two meters in the subsurface of Mars. Among the scientific objectives of the ExoMars mission, the searching of the organics or volatiles species plays an important role. The Ma_Miss spectrometer (Mars Multispectral Imager for Subsurface) [2] will investigate the borehole generated by the drill and it will be able to characterize and map the presence of possible ices. In this work we developed a numerical model to predict the subsurface temperatures after the heat released by the drilling operations. The increase in temperature due to the drilling operations, in fact, could affect the survivor of the volatile species [3]. Here we report the results about subsurface temperature of Oxia Planum. Numerical modeling We developed a numerical modeling to predict the subsurface temperature of Oxia Planum. In the subsurface we solve the classical heat equation [3]: where ρ is the density, c p the specific heat, K the thermal conductivity and T the temperature. Heat transfer occurs only by conduction since convection is negligible due to the small temperature gradients involved as well as the characteristic size of the sample. At the top we imposed a radiation boundary condition. In order to take into account the heat released by the drilling operations we imposed a frictional heating flux on the sides “in contact” with the drill (the lateral sides of the borehole of Fig.1). This flux is defined by the equation [3]: where η is the coefficient of friction, Fn the thrust, ω the rotational velocity, r the radius of the hole and h the height of the domain of integration (in our case 50 cm). The parameters adopted in this work are F n = 300 N, rpm = 30 or 60, η = 0.3 or 0.9, tip density = 3500 kg m-3, tip thermal conductivity = 540 W m-1K-1, tip specific heat = 790 J kg-1K-1 and a drilling window of 90 min, characterized by 30 min in “on mode”, followed by 30 min in "off mode” and finally 30 min in “on mode”. The surface and subsurface of Oxia Planum is characterized by a thermal inertia of 650 TIU, with an initial temperature fixed to 200 K. Some assumptions are made: I) instantaneous drilling(drill excavation is not modeled); 2) constant thrust; 3) constant rotational velocity. Fig.1: Geometry adopted in this work. The borehole of the drilling system is represented by the cylinder embedded in this domain of integration, with a radius of 13 mm (the thickness of the drill tip). In Fig.2 we report an example of 1-D temperature profile at z=50 cm (the maximum depth of the borehole). In the x-axis we report the distance from the hole, where shadowed red rectangle identifies the drill (or equivalently the borehole). Top panel of Fig.2 is characterized by rpm=30 and η=0.3 while the bottom panel by rpm=30 and η = 0.9. From these plots we note a difference, in the maximum value after 90 minutes, of about 40 K in favour of the case with η=0.9. The increase in temperature due to the drilling operations, in case of η=0.9, respect the initial assumed value (200 K) is about 80 K. The initial value of 200 K is chosen since is close to the surface equilibrium temperature value for Mars. As in [4] we can calculate the lifetime of an ice spherical deposit of mass m0, with a radius equal to the radius of the drill tip. The relative loss of ice mass at time (t) after the deposit is raised the temperature T is: where t is the time expressed in seconds. In this equation, Г represent the water rate emission, rp the radius of the tip and рice the density of the ice. By using the maximum sublimation rate, we obtain in case of rpm = 30 and η=0.3 a loss of about 60% of the initial mass, while in case η=0.9 of the loss is complete. In Fig.2 we report an example of temperature internal profile after the heat released by the drilling operations. Both panels refer to rpm=30: top panel is characterized by η=0.3 while bottom panel by η=0.9. Summary and Conclusions. We simulated the heat released by the drilling operations in different case of friction (η) and rotatonal speed (rpm) of the drill. We observed that in case of η=0.3 the maximum temperature increase at a depth of 50 cm is about 55 K (with rpm=30) and about 75 K (with rpm=60), while in case of η=0.9, the maximum temperature increase becomes 90 K (with rpm=30) and 130 K (with rpm=60) [3]. We also calculated the sublimation rate and the lifetime of a hypothetical spherical ice-rich deposit, with a radius equal to the size of the tip of the drill. We obtained that, after 90 minutes from the start of our simulations, in the coldest scenario (η=0.3 and rpm=30) the remaining initial mass is about the 60%, while in the other scenarios we have a complete loss of the mass [3]. Future improvements in the numerical model (e.g. a complete treatment of the diffusion of volatiles) as well as validation with laboratory experiments will be made. Acknowledgments. This work is funded and supported by the Italian Space Agency (ASI) [Grant ASI-INAF n. 2017-48-H.0].References [1] Vago J.L. et al. 2017; [2] De Sanctis M.C. et al 2017; [3] Formisano M. et al. 2021; [4] Andreas E.L. 2007; [5] Coradini A. et al. 2001

Introduction We developed a simple model to simulate Ma_MISS data acquisition and visualization and to support the development of acquisition strategies. The Ma_MISS instrument Ma_MISS (Mars Multispectral Imager for Subsurface Studies) is the miniaturized VNIR spectrometer embedded in the drill system of the ExoMars rover[1]. Ma_MISS will perform spectral reflectance measurements inside holes drilled into the surface of Mars up to a depth of 2 m. It will characterize the mineralogy and stratigraphy of the borehole walls and will allow the in-situ study of the subsurface environment, before any samples are collected and extracted. Taking advantage of the finely controllable drill tool motion, Ma_MISS can map the borehole walls. In addition to single point acquisitions, Ma_MISS can also be programmed to acquire “Ring” and “Column” scans, where the spectrometric acquisitions are interleaved with step rotations or translations of the drill tool. Borehole stratigraphy model To easily simulate Ma_MISS surveys, we first developed a simple model of a borehole. As further described in [2], six different simulant samples were prepared. Reflectance spectra were acquired on each of the samples with DAVIS-MOT, the new Ma_MISS laboratory model[3]. The reflectance spectra of these samples are shown in Figure 1. Six different regions were drawn as polylines on a 2D projection of the cylindrical borehole walls. Out of the six simulants, a different one was assigned to each region. As shown in Figure 2, this model was made to represents a 250 mm deep section of a borehole, exhibiting a varied stratigraphy with 5 different layers and a vertical vein. Figure 1: Reflectance spectra of samples. Figure 2: Borehole stratigraphy model Survey simulation The borehole model can be used to quickly simulate a Ma_MISS survey. Once the acquisition strategy of the survey is defined, the coordinates of the points where spectrometric acquisitions are to be simulated are computed. Small random errors can be added to the coordinates to simulate the accuracy of the drill tool actuators and sensors. For each point of this set, we generate a spectrum that simulates the real acquisition. Each simulated spectrum is generated from the measured spectra of one of the six simulants, based on its region in the stratigraphy model, with the addition of random shifts, slopes, and noise to simulate out-of-focus acquisitions and instrumental noise. Development of acquisition strategies The simulated data can be used to develop acquisition strategies, aimed at maximizing the information gained while limiting the time required to complete a survey of a drilled borehole. The time required to complete the survey depends on both the spectrometer acquisition settings and the drill tool motion. For example, the duration of a drill movement depends on angular and vertical step sizes (hereafter referred to as Δθ and Δz respectively), with vertical translations generally taking longer than rotations. Multiple combination of these parameters can be tried out on the same stratigraphy model to evaluate which strategy can provide the best compromise between spatial resolution and time required. Simulated data examplesFor the 4th RSOWG (Rover Science Operations Working Group) Simulation, held in November 2021, we provided data from a simulated Ma_MISS acquisition survey. The simulated Ma_MISS survey (“survey A”) consisted of: -6 rings of 360 points each, with Δθ=1° and displaced vertically by Δz=50mm; -8 columns made up of 126 points each, taken with Δθ=45° and a vertical step of Δz=2mm.This amounts to a total of 3168 individual spectra. A view of the simulated data is shown in Figure 3 and Figure 5A. This acquisition strategy provides a high angular resolution in the rings with Δθ=1° (which can be useful to identify small vertical features or individual grains) and a good vertical resolution in the column with Δz=2mm (useful to reconstruct the stratigraphy of the subsurface). Another survey (“survey B”) that was simulated with the same model is shown in Figure 4 and Figure 5B-C. In this case the acquisition was made up of 35 rings of 72 points each, with Δθ=5° and Δz=6.25 mm, for a total of 2952 spectra. This strategy offers worse spatial resolution in both the vertical direction and along the circumference but can nonetheless provide a more regular overall view of the borehole stratigraphy. Figure 3: Simulated survey A Figure 4: Simulated survey B Data visualization In Figure 3 and 4, each dot represents a simulated spectrum. In this case the colour of each dot was computed from its spectrum such that it looks somewhat like it would appear to the human eye. The same colours were interpolated across the surface (with a scattered data bicubic interpolation method) to obtain views like those shown in Figure 5A-B. Other useful visualizations of these spectra can be obtained by highlighting other spectral features, e.g., band depths, band ratios or specific IR bands. An example is shown in Figure 5C, where the 1.95 µm band depth is computed on the simulated spectra of survey B and its value is interpolated across the cylindrical surface. Figure 5: Visualization of simulated data on the borehole surface Future work The developed simulation model can be easily extended to other borehole stratigraphy models, with different geometries and spectra. It will also be complemented with tools to estimate the time needed to perform each simulated survey, which will make it a useful tool for the optimization of acquisition strategies. The developed data visualization tools can also be used with real, measured data. We are planning to verify the simulated data on real surveys. In fact, we can perform a complete survey with the Ma_MISS laboratory breadboard on an actual drilled sample. The acquired data will be visualized and used to reconstruct the sample stratigraphy. Acknowledgments This work is supported by the Italian Space Agency (ASI) grant ASI-INAF n. 2017-412-H.0. References[1] De Sanctis M.C. et al. (2017): Astrobiology, 17, 6-7[2] Ferrari M. et al. (2022): LPSC53, Abstract#1339[3] De Angelis S. et al. (2022): LPSC53, Abstract#1796

Introduction: ExoMars rover Rosalind Franklin will search for traces of past or present life potentially preserved in the designated landing site Oxia Planum [1]. Oxia is located in the western part of Arabia Terra, where geology shows evidence of a past long-lived liquid water body [2]. This clay-bearing plain is overlapped by deltaic system material provided by channels of Coogoon Valles. Spectral detections underlie the possible presence of Fe-rich phyllosilicate (for example vermiculite) and Mg-rich phyllosilicate (for example saponite) mixed with a variable amount of olivine. A mafic coating-resistant unit seems to be present [3,4,5]. Many minerals are expected to be analyzed by the Ma_MISS (Mars Multispectral Imager for Subsurface Studies) instrument at the landing site. The drill is also made up of three extensible 50 cm-long rods. The instrument is a VNIR (0.4–2.3 µm) miniaturized spectrometer in-stalled into the rover drill’s tip. It will acquire borehole spectral images in situ to study the subsurface mineralogy up to 2 m depth with a spatial resolution of 120 µm for looking at organics traces. Ma_MISS is composed of the Optical Head with fibres into the tip and the other fibres in the rods, while the spectrometer and the electronic are outside on the drill box. The sapphire window in the main rod allows the 5W light to illuminate inside the borehole and the reflected signal to be acquired by the spectrometer. The light illuminates a 1 mm diameter spot at ~0.6 mm focal distance. Thanks to drill rotation and vertical movement, Ma_MISS can collect several points to reconstruct a complete borehole image [1]. Laboratory breadboard: Drill for Analogues and Visible-Infrared Spectrometer (DAVIS) is the recent laboratory setup consisting of Laboratory Drill (DAVIS-LD) and Ma_MISS Optical Tool (DAVIS-MOT) (Figure 1). The first one (LD) is the replica of the rover drill except for the spectral acquisition system. The vertical motion is actuated by a hand lever to drill a hole in the rock samples. The motor unit is the same as the flight model but the controller is a commercial EC motor, which control the rotational speed (50 rpm) [6]. The second one (MOT) comprises a 75 cm-long and 25.4 mm-diameter rod, 5W lamp, Sapphire window, Optical Head, and an optical fibre. It is the copy of rover Ma_MISS except for the drilling ability. In this case, rover spectrometer is replaced with two Avantes VIS-NIR spectrometers. The Optical Head fibre is connected with the Avantes fibre through a mini-Avim connector. Being a replica of Ma_MISS, the light spot has 1 mm diameter at ~0.6 mm focal distance and the spatial resolution is 120 µm. It acquire in two different configurations: 1) Slab or powder samples are hosted in a vertical three-axis sample-holder and 2) manual motion of the rod to enter in the sample borehole [7]. Figure 1 – a) Ma_MISS Optical Tool (DAVIS-MOT) and b) Laboratory Drill (DAVIS-LD). Martian Analogue sample: The Martian analogue denominated CAP-1 was collected during a geological survey of the Institute for Space Astrophysics and Planetology (IAPS), in October 2021. It was gathered in 120 cm-depth excavated trench in the area of Capalbio (Tuscany, Italy). It is a Pleistocene metasedimentary rock subjected to hydrothermal alteration/weathering (Figure 2). This brownish siltstone/mudstone is a quite compact rock in dry conditions and brittle in wet conditions. Inside it, there are a few discoidal, sub-angular grains with a diameter higher than 2 mm and different colors (black, reddish, and white), and low sphericity. Grains are not-oriented, except for black Manganese aggregates, which form thin veins with a diameter of about 2-5 mm. Other grains are white rectangular precipitations of Al-bearing clay (kaolinite) and reddish irregular aggregates formed by iron oxide (hematite). The brownish fine-grained (granulometry in the order of silt-clay) matrix has medium porosity, without cement. It lacks stratification and it shows possible alteration due to iron oxidation. CAP-1 is well-sorted, texturally and compositionally mature. The mineral assemblage of the CAP-1 sample is constituted of Mg/Fe smectite, kaolinite, illite, quartz, and minor calcite. It can contain some part of organic material based on analysis of similar soil in the area, but no detectable fossil evidence is found inside. Figure 2 – a) Outcrop where CAP-1 is extracted (sampling depth 30-75 cm); b) Sample Capalbio CAP-1; c) Details of CAP-1 taken under a microscope: Mn aggregates. Discussion and conclusions: Some preliminary acquisitions are taken using the DAVIS-MOT, as we can see in Figure 3. We acquire 3 random points on a planar surface of the sample. After that, raw data of spectra are smoothed and merged between 1075 and 1140 nm (the AVANTES spectrometer has two different detectors and the acquisitions are made for the VIS and IR in two steps). Resampling is done in 364 points between 400 and 2300 nm. Spectra show characteristic absorption bands of water at 1.4 and 1.9 µm, well-shaped absorption bands at 0.95 and 2.2 µm associated with iron transition and Al-OH bond respectively. A deep spectral analysis will be done after the new laboratory acquisition of this sample. Figure 3 – VIS-NIR CAP-1 spectra acquired by DAVIS-MOT. Acknowledgments: This work is supported by the Italian Space Agency (ASI) grant ASI-INAF n. 2017-412-H.0. Ma_MISS is funded by ASI and INAF. References: [1] De Sanctis, M. C. et al. (2017) Astrobiology, 17(6–7), doi: 10.1089/ast.2016.1541; [2] Davis, J. M. et al. (2016) Geology, 44(10), doi: 10.1130/G38247.1; [3] Quantin-Nataf, C. et al. (2021) Astrobiology, 21(3), doi: 10.1089/ast.2019.2191; [4] Mandon, L. et al. (2021) Astrobiology, 21(4), doi: 10.1089/ast.2020.2292; [5] Brossier, J. (2022) Icarus, accepted pending revisions; [6] Rossi, L. et al. (2022) LPSC 53, Abstract #1353, [7] De Angelis, S et al. (2022) LPSC 53, Abstract #1796.

In this work, we apply a method previously discussed in [1] to assess the presence of water ice in Mercury’s Polar Shadowed Regions (PSR) mixed to S-rich volatile species like SO2, H2S, and volatile organics, intending to verify their detectability from Bepi Colombo’s orbit and to optimize SIMBIO-SYS/VIHI observations. PSR icy deposits located within the floor of the Kandinsky crater are simulated in terms of I/F spectra corresponding to mixtures of H2O-H2S and H2O-SO2 with grain sizes of 10, 100, and 1000 µm as resulting from indirect illumination by the scattered solar light coming from the crater’s rim. The spectral simulations, performed following the method described in [2], and including the ice-regolith mixing (areal or intimate) as modeled in [3], allow for exploring different volatile species abundances and grain size distribution.The resulting ice detection threshold are evaluated by means of the computation of VIHI’s instrumental signal-to-noise ratio as given by the instrumental radiometric model [4]. In this way, a synergistic use of illumination models, spectral simulations and resulting SNR calculations will help us to optimize the VIHI’s observation strategy across Mercury’s polar regions with the aim to detect, identify and map volatile species. This task is one of the primary scientific goals of the 0.4-2.0 µm Visible and Infrared Hyperspectral Imager (VIHI) [5], one of the three optical channels of the SIMBIO-SYS experiment [6] on ESA’s BepiColombo mission.Due to orbital characteristics and proximity to the Sun, Mercury’s polar regions undergo large variations in illumination conditions during the hermean year [1]. At poles, Permanent Shadowed Regions (PSRs) occur on deep craters and rough morphology terrains that are not directly illuminated by the Sun during the hermean day. Nevertheless, some of these areas could experience partial illumination caused by multiple scattered light coming from nearby illuminated areas. Despite the orbital vicinity to the Sun, Mercury’s PSRs can maintain cryogenic temperatures across geological timescales resulting in the condensation and accumulation of volatile species [7]. While water ice is the more certain species in Mercury’s PSR, it is not precluded the occurrence of other secondary species rich in sulfur or even organic matter.In fact, the total surface area of PSRs between latitudes 80−90° south is not negligible, being estimated at about 25.000 km2 [8], about two times larger than the same geographic area on the North Pole [9]. References: [1] Filacchione G. et al., MNRAS, 498, 1308-1318, 2020. [2] Raponi A. et al., Sci. Adv., 4, eaao3757, 2018. [3] Ciarniello. M. et al., Icarus, 214, 541, 2011. [4] Filacchione G. et al., Rev. Sci. Instrum., 88, 094502, 2017. [5] Capaccioni F. et al., IEEE Trans. Geosci. Remote Sens., 48, 3932, 2010. [6] Cremonese G. et al., Space Sci. Rev., 216, 75, 2020. [7] Paige D. A. et al., Science, 339, 300, 2013. [8] Chabot N. L. et al., J. Geophys. Res., 123, 666, 2018. [9] Deutsch A. N. et al., Icarus, 280, 158, 2016. Acknowledgments: We gratefully acknowledge funding from the Italian Space Agency (ASI) under ASI-INAF agreement 2017- 47-H.0.

The current generation of rovers exploring Mars for traces of life feature tools for subsurface sampling capabilities. This addition to the sampling capabilities of the martian rovers is crucial for the search for life. In fact, in the subsurface life is more likely to be protected from the harsh radiation environment present on the surface. The sampling of subsurface materials started with the analysis of the first millimeters of unweathered rocks being pulverized or abraded (NASA/MSL), evolved with the extraction of small cores from the first 10 centimeters (NASA/Mars2020), and will continue with the exploratory drilling of ESA's ExoMars 2022 which is capable of reaching 2 meters of depth. The proper planning and interpretation of measurements below the topographic surface require a model of the subsurface. Geological models are digital representations of subsurface structures generated by the sequence in time of processes putting in place different rocks and terrains. Geologic cross-sections are an example of bi-dimensional modeling that extends observations taken at the surface. Modern geologic models are commonly developed in three dimensions and used for terrestrial resource exploration, seismic analyses, and hydrologic simulations. The key to a good geologic model is the integration of measurements taken by different instruments. For ExoMars 2022, observations at the surface will be extended at depth by the spectrometer Ma_MISS which will read the mineralogical composition down to two meters, and the radar WISDOM which will collect geophysical images of the terrain down to ten meters or more. In this work, we explore different methods to generate geological models of the subsurface of areas at Oxia Planum and a selection of analog outcrops at different scales.

The ExoMars Rover and Surface Platform planned for launch in 2022 is a large international cooperation between the European Space Agency and Roscosmos with a scientific contribution from NASA. Thales Alenia Space is the ExoMars mission industrial prime contractor. Besides sensors and instruments characterizing the surface at large scale, the ExoMars’ rover Rosalind Franklin payload features some experiments devoted specifically to the characterization of the first few meters of the Martian subsurface. These experiments are particularly critical for the main ExoMars objective of detecting traces of present or past life forms on Mars, which may have been preserved within the shallow Martian underground [1]. Rosalind Franklin will be able to perform both non-invasive geophysical imaging of the underground [2] and subsurface in situ measurements thanks to the Drill unit installed on the rover. The Drill has been developed by Leonardo and its purposes are 1) to collect core samples to be analyzed in the Analytical Laboratory Drawer (ALD) onboard the Rover and 2) to drive the miniaturized spectrometer Ma_MISS within the borehole. Ma_MISS (Mars Multispectral Imager for Subsurface Studies, [3]) will collect mineralogic measurements from the rocks exposed into the borehole created by the Drill with a spatial resolution of 120 μm down to 2 meters into the Martian subsurface. Rocks are composed of grains of minerals, and their reaction to an applied stress is related to the mechanical behavior of the minerals that compose the rock itself. The mechanical properties of a mineral depend mainly on the strength of the chemical bonds, the orientation of crystals, and the number of impurities in the crystal lattice. In this context, the integration of Ma_MISS measurements and drill telemetry are of great importance. The mechanical properties of rocks coupled with their mineralogic composition provide a rich source of information to characterize the nature of rocks being explored by ExoMars rover’s drilling activity. Within our study, we are starting to collect telemetry recorded during the Drill unit tests on several samples ranging from sedimentary to volcanic rocks with varying degrees of weathering and water content. In this first phase of the study, we focused our attention on the variation of torque and penetration speed between different samples, which have been found to be indicative of a particular type of rock or group of rocks and their water content. We are planning to analyze the same rocks with the Ma_MISS breadboard creating the link between the mineralogy and the mechanical response of the Drill. This will put the base for a more comprehensive and rich characterization of the in situ subsurface observation by Rosalind Franklin planned at Oxia Planum, Mars in 2023. Acknowledgments: We thank the European Space Agency (ESA) for developing the ExoMars Project, ROSCOSMOS and Thales Alenia Space for rover development, and Italian Space Agency (ASI) for funding the Ma_MISS experiment (ASI-INAF contract n.2017-48-H.0 for ExoMars MA_MISS phase E/science). References [1] Vago et al., 2017. Astrobiology, 17 6-7. [2] Ciarletti et al., 2017. Astrobiology, 17 6-7. [3] De Sanctis et al., 2017. Astrobiology, 17 6-7.

Introduction Alteration of mafic and ultramafic rocks on Mars surface and shallow subsurface has been postulated to have occurred throughout its history by means of different mechanisms, among which acid groundwater circulation (mainly sulfuric) is one of the most important [1,2,3,4]. This hypothesis is based on the high Fe and S concentration observed at various landing sites and strengthened by remote-sensing infrared detection of Fe/Al-bearing sulfates such as alunite, jarosite and Fe3+SO4(OH) [4,5]. These sulfates typically form as alteration of K-rich volcanic rocks and Fe-sulfides in low-pH environments. Additionally the occurrence of perchlorates could be related to the action of other acids (perchloric) [6]. The investigation in laboratory of acidic alteration of volcanic rocks is thus an essential step in order to provide constraints in the interpretation of remote-sensing and in-situ data from Mars missions of the next future (Mars-2020, ExoMars-2022). Several works recently have explored the processes of acid alteration of minerals and rocks both in the field and in laboratory by using different spectroscopic and microscopy techniques [7,8]. Methods In our work we studied by Visible-Near Infrared reflectance and Raman spectroscopy the acid alteration of two volcanic samples, a basalt from Aeolian Islands (FCD1) and a rhyodacite from Alps (RDO). These two samples have been chosen with the aim of investigating the action of acids on both a mafic and a felsic rock. Four acids have been used for the treatment of samples, namely hydrochloric (HCl 37 vol%), nitric (HNO3 65 vol%), sulfuric (H2SO4 96 vol%) and phosphoric (H3PO4 85 vol%), in order to contemplate a diversity of acid environments. Samples were acid-treated both in the form of fine powders (d VIS-NIR reflectance spectroscopy measurements were carried on with ASD FieldSpec-4 spectro-photometer coupled with a QTH lamp and optical fibers (i=30°, e=0°), in the 0.35-2.5-μm range, using LabSphere Spectralon as reference. The spectral sampling was 3-8 nm, and the spatial resolution about 6 mm. Raman spectroscopy data were acquired with a Bruker-Senterra II spectrometer, with a 532 nm excitation laser, a power of 50 mW, 4 cm-1 spectral resolution, and about 5 mm of spatial resolution. Raman data were acquired on pre- and post-treatment slab samples. Results VIS-NIR. We present preliminary results of our experiments. Example of VIS-NIR spectra are shown in fig.1 for the basalt FCD1. The spectrum of pre-treated basalt (black curve, fig.1) is characterized by iron absorption features at 0.52 μm and 1 μm (faint), with a blue slope below 1.5 μm and a red slope above 1.5 μm. Although the effect due to some hydration is unavoidably present in the treatment, nevertheless the different acids produce different results. The overall spectral shape does not change much after treatment with HCl and HNO3, although new absorption features appear or increase in intensity. In the HCl-treated sample the 1-μm band is notably more marked than the pre-existing one, and new features appear at 1.44, 1.60, 1.75, 1.93, 2.15 and 2.24 μm. Although especially the ~1.4 and ~1.9-μm bands are related to hydration in the sample or to some new hydrated phase, nevertheless these new bands indicate the appearance of new mineralogical phases. For example some of these bands are reported to occur in hydrated Na-perchlorates [9]. Curiously in the HCl-treated sample the ~0.5-μm feature seems to disappear. In the H2SO4-treated sample the overall spectral slope is changed from red to blue, and only two hydration bands appear. In the HNO3-treated sample a new weak band appeared around 2.23 μm. Raman. The Raman spectra of an alkali-feldspar phenocryst of the rhyodacite sample (RDO) collected pre- and post-treatment with HNO3 are displayed in fig.2 (black and red, respectively). The spectrum of the untreated sample is characterized by the typical Raman peaks of the alkali-feldspar. On the contrary, in the spectrum of the acid-treated sample, the appearance of the peaks at 1053 and 715 cm-1 indicate the formation of niter (NaNO3) in the same areas of the sample where the alkali-feldspar is present. Conclusions Visible-infrared and Raman analyses of both mafic and felsic volcanic rocks treated with different acids have shown the appearance of new absorption bands and changes in spectral shapes, indicating the formation of new mineralogical phases. While Raman data clearly indicate the presence of precise minerals, the interpretation of VIS-NIR spectra is not straightforward. Further analyses will be conducted both on the powders and slabs in order to recognize the new mineralogical phases, to discriminate between the alteration action of acid solution and water alone, and to disentangle the effects of the different acids over time. Acknowledgements This work is funded by ASI. We thank A.Pisello from University of Perugia for providing the rhyodacite sample. References. [1] Burns R.G., Journal of Geophysical Research, vol.92, n.B4, pp.E570-E574, 1987 [2] Burns R.G., 19th Lunar and Planetary Science Conference, 46-47, 1988 [3] Burns R.G. and Fisher D.S., Journal of Geophysical Research, vol.95, n.B9, pp.14,415-14,421, 1990 [4] Hurowitz J.A. and McLennan S.M., Earth and Planetary Science Letters, 260, 432, 443, 2007 [5] Ehlmann B.L. and Edwards C.S., Annu. Rev. Earth Planet. Sci., 42, 291-315, 2014 [6] Wilson E.H., Journal of Geophysical Research:Planets, 121, pp.1472-1487, 2016 [7] Gurgurewicz J. et al., Planetary and Space Science, 119, 137-154, 2015 [8] Smith R. et al., Journal of Geophysical Research:Planets, 122, pp.203-227, 2017 [9] Hanley J. et al., Journal of Geophysical Research:Planets, 119, pp.2370-2377, 2014

We studied the dust activity of comet 67P/Churyumov-Gerasimenko (67P), by relating the detections of the Rosetta/ GIADA and MIDAS instruments, obtaining a correlation between flux of ejected mm- and μm-sized dust. Introduction The ESA/Rosetta mission orbited the 67P comet for two years, escorting it through perihelion, occurred on 13th August 2015. The mission configuration is still permitting a thorough characterization of cometary activity, even 4 years from the end of the mission. In particular, the 67P’s dust ejection has been detected in different stages of the comet’s orbit by both remote observations (e.g., the OSIRIS camera and the VIRTIS imaging spectrometer) and in-situ measurements performed by detectors as GIADA, MIDAS and COSIMA. This work merges data from the GIADA (Grain Impact Analyser and Dust Accumulator) [1] dust detector and the MIDAS (Micro-Imaging Dust Analysis System) [2] atomic force microscope. The two instruments detected dust different in size (mm-sized vs μm-sized) and complementary dust properties (porosity and mass vs physical properties and 3D structure). The GIADA and MIDAS data fusion could allow to relate ejection of smaller and larger dust particles as well as to monitor variations of dust properties during Churyumov-Gerasimenko’s orbit and to link them to the morphology of ejecting surface regions. Data 2.1 The GIADA dataset The GIADA instrument consists of three subsystems: Grain Detection System (GDS), Impact Sensor (IS) and Quartz Crystal Microbalances (QCM). The first two subsystems measured velocity of fluffy particles and momentum of compact (mm-sized) particles, respectively, whereas the QCM measured the cumulative mass of nm-sized dust [3]. To compare GIADA and MIDAS dataset, we considered only the IS data, because MIDAS mostly detected individual compact particles. In particular, we considered only the IS detections acquired in the periods when MIDAS detected dust particles (see next subsection). [4] developed a procedure to trace back the motion of dust particles detected by GIADA in the coma down to the nucleus surface. This allowed the retrieval of the geomorphological region ejecting each dust particle and the association of dust and surface properties. These results are intended to be extended to the GIADA-MIDAS data fusion to relate dust physical properties and surface morphology. 2.2 The MIDAS dataset MIDAS collected micron-sized dust particles on several targets, each working in a defined period. Cometary dust was detected on four MIDAS targets: Target 10, Target 12 and Target 14 collected dust in three periods before perihelion (September-November 2014, December2014-February 2015 and February-March 2015, respectively), whereas the dust collected on Target 13 was released in an outburst on 19th February 2016 (after perihelion). Except one case of a fluffy agglomerate [5], all the particles detected by MIDAS are compact. Method and preliminary results 3.1 mm- vs μm- sized dust flux Our first step was to compare the millimetric and micrometric dust flux measured by GIADA-IS and MIDAS, respectively. For each period corresponding to the collection time of a MIDAS target, we retrieved the number of particles detected by the two instruments, normalized it to the period duration (in days) and to the spacecraft-comet distance (in km). The MIDAS flux required an additional normalization, taking into account the scanned area on the respective target (not constant among targets). The comparison of dust fluxes measured by GIADA and MIDAS is shown in Figure 1. Figure 1. Dust fluxes measured by MIDAS and GIADA. Each asterisk corresponds to a MIDAS target, i.e., to a defined orbit period. The red asterisk corresponds to MIDAS Target 14 (which detected dust between February and March 2015). The flux logarithms are linearly related, suggesting a strong correlation between ejection of large (mm-sized) and small (mm-sized) compact dust agglomerates. The flux corresponding to the MIDAS Target 14 period (February/March 2015), highlighted in red in Figure 1, is slightly outside this linear trend, with GIADA (MIDAS) detecting more (less) particles than expected from the linear trend identified by the other three periods. This can be ascribed to the occurrence of an outburst (detected by GIADA but not by MIDAS) in a moment when the spacecraft had the largest distance to the comet among all herein considered periods. As smaller particles are stronger deviated from their initially radial trajectory than larger ones (due to the more important role of solar pressure force with respect to nucleus gravity [6]), it is reasonable that fewer small than large particles arrived at the spacecraft position. However, this result needs further refinement regarding a possible falsification of MIDAS particle size distribution caused by particle fragmentation upon collection. Our next steps are to discern parent particles and fragments in the MIDAS data set and to update the relation shown in Figure 1. This will be done by analyzing the spatial distribution of dust particles on the MIDAS targets, by comparing MIDAS’ dust size distribution to that expected during nominal activity [7] and during outbursts [8] and by taking into account the largest dust size expected to be ejected depending on the nucleus surface temperature [9]. 3.2 Dust vs surface properties By applying the traceback algorithm developed by [4], we obtained that in certain periods dust is mostly ejected from rough or from smooth terrains. Therefore, we can relate properties of particles stemming from different locations at the comet to cometary surface morphology. In addition, dust ejected during outbursts may probe deeper layers of the comet, allowing us to discern dust properties at different depths. Acknowledgements This research was supported by the Italian Space Agency (ASI) within the ASI-INAF agreement I/032/05/0, by the Austrian Science Fund FWF P 28100-N36, and by the International Space Science Institute (ISSI) through the ISSI International Team “Characterization of cometary activity of 67P/Churyumov-Gerasimenko comet”. References [1] Della Corte, V. et al. (2014) JAI 1350011-1350022; [2] Bentley, M.S. et al. (2016), Acta Astronautica 125; [3] Della Corte, V. et al. (2019), A&A 630, A25, 13 pp.; [4] Longobardo, A. et al. (2020), MNRAS 496, 1, 125-137; [5] Mannel, T. et al. (2016), MNRAS 462; [6] Zakharov, V.V. et al. (2018), Icarus, 312, 121-127; [7] Rinaldi, G. et al. (2016), MNRAS 462, 1, S547-S561; [8] Bockelée-Morvan, D. et al. (2017), MNRAS, 469 2, S443-S458; [9] Fulle, M. et al. (2020), MNRAS, 493, 4039-4044.

We performed thermophysical simulations of Oxia Planum, the landing site of the ExoMars 2022 mission [5]. The numerical simulations concern: I) the influence of the thermal inertia on the subsurface temperature at the latitude of Oxia Planum; II) the heat released in the subsurface by the drill installed on the ExoMars rover. The numerical simulations are performed using a 3-D model using the discretization technique of the finite element method (FEM). 1. Introduction Numerical simulations are required to characterize, from a thermophysical point of view, Oxia Planum, the landing site of the mission ExoMars 2022. A drilling system is installed on the ExoMars rover and it will be able to analyze up 2 meters in the subsurface of Mars. The spectrometer Ma_Miss (Mars Multispectral Imager for Subsurface) [1] will investigate the lateral wall of the borehole generated by the drill, providing hyperspectral images. Among the scientific objectives of Ma_Miss there are the characterization and the mapping of possible volatiles. In this regard, numerical simulations are useful to understand if the temperatures in the subsurface are such as to preserve volatiles, especially after the heating provided during the drilling operations. 2. Numerical Method We performed our simulations by using a 3-D finite element model [2, 3], which solves the classical heat equation in a parallelepipedal domain representing a portion of Oxia Planum, the landing site of the ExoMars mission. The top of this domain is modeled with a Gaussian random surface in order to simulate the roughness of the surface. The dimensions of the domain are 1cm x 1cm x 5cm. The depth (5 cm) has been chosen since it is compatible with the likely skin depth. At the top we imposed a radiationboundary condition, while on the other sides zero heat flux is imposed. The initial temperature is set at 200 K, which is compatible with the surface equilibrium temperature. Self-heating between the facets of our domain is taken into account. We investigate: I) the dependence of the subsurface thermal response to different thermal inertia; II) theheat released by the drill in the subsurface of Mars. In particular, for the point II, we assume: a) the drilling is instantaneous in a well-defined “drilling temporal window”; b) thrust and rotational velocity are constant. The contribution of the drill is taken into account by applying an heat flux (depending in particular on the thrust, angular velocity and frictional heating) on the wall of the rock matrix in contact with the drill. 3. Summary and conclusions In Fig.1 we report an example of the results we obtained by applying our numerical model. Fig.1 shows the temperature profile vs time at different depths for two cases: case Fig.1: Temperature profile vs time at different depths. Case (A): K = 0.045 W m−1K−1; Case (B) K = 0.0045 W m−1K−1. (A) with a thermal conductivity K=0.045 W m-1 K-1, compatible with Insight estimation [4] and case (B) with a thermal conductivity an order of magnitude smaller than the case (A). Case (A) is characterized by a thermal inertia of 270 TIU (Thermal Inertia Units) and a skin depth of 3 cm, while case (B) is characterized by a thermal inertia of 85 TIU and a skin depth less than 1 cm. Our numerical results suggest that: a) the surface temperature ranges from 180 K to 270 K if thermal inertia is high (300 TIU); b) surface temperature ranges from 140 K to 280 K if thermal inertia is low ( Fig.2: Left panel: rpm = 30 and η= 0.5; right panel: pm = 60 and η= 0.9. Acknowledgements The Italian Space Agency (ASI) has founded the experiment. References [1] Coradini, A., et al.: MA_MISS: Mars multispectralimager for subsurface studies, Advances in Space Research, Volume 28, Issue 8, p. 1203-1208, 10.1016/S0273-1177(01)00283-6, 2001 [2] M. Formisano, M.C. [De Sanctis], S. [De Angelis], J.D. Carpenter, and E. Sefton-Nash. Prospecting the moon: Numerical simulations of temperature and sublimation rate of a cylindric sample. Planetary and Space Science, 169:8 – 14, 2019. [3] Rinaldi, G., Formisano, M., Kappel et al., Analysis of night-side dust activity on comet 67p observed by virtis-m: a new method to constrain the thermal inertia on the surface. A&A, 630:A21, 2019. [4] T. Spohn et al. The Heat Flow and Physical Properties Package (HP3) for the InSight Mission, Space Science Reviews volume 214, Article number: 96 (2018) [5] Vago et al., 2017. Astrobiology, 17 6-7

Laboratory measurements were performed on different mixtures made with clays and organic compounds with the aim of characterizing the detection capabilities of biosignatures by the Ma_MISS (Mars Multispectral Imager for Subsurface Studies) instrument. Introduction The main scientific objectives of the ESA mission ExoMars2022 are searching for signs of past and/or present life on Mars and characterizing the subsurface geochemical environment as a function of depth. The Rosalind Franklyn rover [1] payload consists of a suite of nine instruments that will provide information about the geological and geochemical environment of the surface and subsurface of the selected landing site (i.e. Oxia Planum) [2]. Remote sensing measurements performed by OMEGA and CRISM suggest that the exposed rocks on the surface of Oxia Planum experienced an intense aqueous alteration [3]. The widespread presence of Fe/Mg-Al-phyllosilicates and, more generally, the presence of silicates containing OH confirm the interaction between water and mother rocks, which is a prerequisite favorable to the development of life. In this framework, we performed several spectroscopic measurements of clay minerals mixed with different organic compounds, to assess Ma_MISS capability of organic’s detection in the Martian subsurface. The Ma_MISS instrument Ma_MISS is the Visible- and Near-Infrared miniaturized spectrometer hosted in the drill system of the ExoMars2022 rover that will characterize the mineralogy and stratigraphy of the excavated borehole wall at different depths (2O and hydrated phases; (3) characterize important optical and physical properties of the materials (e.g., grain size); (4) produce a stratigraphic column that will provide information on the subsurface geology. Ma_MISS will operate periodically during pauses in drilling activity and will produce hyperspectral images of the drill’s borehole. Experimental setup The characterization of the scientific performances of the Ma_MISS instrument was made using the laboratory model (breadboard, Fig. 1 [5], [6]) at the Institute for Space Astrophysics and Planetology – INAF. The Ma_MISS breadboard includes the 5 W light source, the optical fibers, and the Optical Head with the dual task of focusing the light on the target and recollecting the scattered light. However, it does not include the flight spectrometer and is therefore coupled with a laboratory spectrometer (FieldSpec 4). Fig. 1: Ma_MISS breadboard setup. A: Ma_MISS Optical Head; B: sample holder. Clay/organic mixtures measurements For these tests we prepared numerous samples mixing two clay minerals (nontronite and kaolinite) with four different organic compounds (asphaltite, glycine, benzoic acid, and polyoxymethylene). In particular, starting from the pure clay endmembers we tested two cases. In the first case, we added separately asphaltite and glycine in the following percentages: 25, 50, and 75, producing six different samples with high organics concentration. In the second case, we added separately benzoic acid and polyoxymethylene in percentages of 1, 5, and 10% preparing a set of six samples at a low concentration of organics. All mixtures with a grain size < 60 μm were measured using the Ma_MISS breadboard setup collecting reflectance spectra in the range 0.5–2.3 μm. Figure 2 shows an example of the data collected on the mixtures between kaolinite and glycine. Starting from the spectra of the pure clay (kaolinite 100%, black spectrum in Fig.2) and increasing the content of glycine by step of 25 wt.%, the band at 1.4 μm associated to the presence of the OH bond in kaolinite decreases. At the same time the band at 2.1–2.2 μm linked to the Al–OH bond in kaolinite become wider and much stronger due to the superimposition of the wider CH band of glycine at 2.1–2.25 μm. Other mixtures with other types of organics in a concentration below the 1% are still in preparation with the aim of determining the lower detection limit of the instrument in the function of the different hosting minerals. In these tests, we used glycine and other organic compounds, as examples of organic compounds that show absorption features in the VIS-NIR range, although we do not expect to find these specific organics in the Martian subsurface. Fig. 2: Example of Ma_MISS breadboard measurements of mineral/organic mixtures (kaolinite-glycine) in variable proportion. Conclusions Laboratory investigations have been performed using the Ma_MISS breadboard model (coupled with a FieldSpec Pro) on mineral/organic mixtures in different proportions. Spectroscopic measurements collected on these mineral/organic mixtures are useful to characterize Ma_MISS instrument sensitivity in detecting traces of life intimately mixed with minerals that could be present in sedimentary sequences or in hydrothermal products in the Martian subsurface, which is one of the main scientific objectives of the ExoMars2022 mission. The obtained results show that the Ma_MISS instrument can give hints of the presence of organics in the Martian subsoil, as well as characterizing the mineralogy of the drilling site. Moreover, the selected minerals and organic compounds allow us to test the instrument with both dark and bright samples. The spectra obtained during these tests will allow us to build a spectral database useful for the interpretation of the scientific data. Acknowledgments We thank the European Space Agency (ESA) for the ExoMars Project, ROSCOSMOS and Thales Alenia Space for rover development, and Italian Space Agency (ASI) for funding and fully supporting Ma_MISS experiment. References [1] Vago J.L. et al. (2017): Astrobiology, 17, 6, 7. [2] Quantin C. et al (2016) #2863, 47th LPSC, Houston, TX. [3] Carter J. et al. al (2016) #2064, 47th LPSC, Houston, TX. [4] De Sanctis M.C. et al. (2017): Astrobiology, 17, 6, 7. [5] De Angelis S. et al. (2014): PSS, 101, 89-107. [6] De Angelis S. et al. (2017): PSS, 144, 1-15.