adsabs/AstroCLIMB huggingface dataset:
Paper: NASA’s Double Asteroid Redirection Test (DART): Mutual Orbital Period Change Due to Reshaping in the Near-Earth Binary Asteroid System (65803) Didymos
Authors: Ryota Nakano, Masatoshi Hirabayashi, Harrison F. Agrusa, Fabio Ferrari, Alex J. Meyer, Patrick Michel, Sabina D. Raducan, Paul Sánchez, Yun Zhang
Figure caption: Histogram for the orbital period change when Dimorphos reshapes. The maximum reshaping parameter is ﹩{\gamma }_{{\rm{\max }}}^{B}=1.05﹩. The black solid and dashed lines indicate the mean and standard deviation, −27.5 and 13.9 s, respectively.
Paper: NASA’s Double Asteroid Redirection Test (DART): Mutual Orbital Period Change Due to Reshaping in the Near-Earth Binary Asteroid System (65803) Didymos
Authors: Ryota Nakano, Masatoshi Hirabayashi, Harrison F. Agrusa, Fabio Ferrari, Alex J. Meyer, Patrick Michel, Sabina D. Raducan, Paul Sánchez, Yun Zhang
Figure caption: Histogram for the orbital period change when Didymos reshapes. The maximum reshaping parameter is ﹩{\gamma }_{{\rm{\max }}}^{A}=1.005﹩. The black solid and dashed lines indicate the mean and standard deviation, −43.9 and 11.5 s, respectively.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: Comparison of rendered features with OLA and SPC data. Each column shows the truth image and feature renderings for the five features tested for both OLA and SPC. Row 1 shows the truth image search region rendered using relative albedo data, while row 2 shows the same image search region rendered with uniform albedo data. This was done to evaluate impacts of feature albedo modeling on performance. Gray circles in row 1 images indicate the exaggerated albedo structures present in Shape 3 (which were later resolved for Shape 4). Row 3 shows rendered OLA features using uniform albedo, Row 4 shows rendered SPC features using relative albedo, and Row 5 shows the same SPC features rendered with uniform albedo. All renderings are for a 55° Sun incidence angle.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: Correlation score for given image conditions for four representative features from the SPC Thread Test. Each point represents a valid correlation result (no false matches) from testing each feature against all images in which the feature was visible and is colored by correlation score (NCC, Normalized Cross-Correlation). The plots in the top row represent features that consistently have high correlation scores for a wide range of image conditions (25°–85° incidence and 20°–55° emission angles), whereas the results in the bottom row are more variable.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: Correlation performance vs. incidence angle from the SPC Stress Test. A “passing” correlation score was 0.6 or higher, while the target pixel error was 6 pixels (3σ) or less. (a) Correlation score performance. (b) Correlation pixel error performance. In both panels, the upper and lower bounds of the blue boxes represent the 75th and 25th percentiles, respectively; the central red mark represents median; the whiskers represent the minimum and maximum data points that are not considered outliers; and the horizontal red dotted line represents the test success criteria.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: Feature correlation challenges and mitigation approach for smoother terrain. Results shown are from the OLA Albedo Test, using Shape 4. (a) The rendered feature and truth image subsection for a very low scoring feature from the test. This feature never scored higher than 0.3, even when the feature DTM and albedo were defined from truth data. (b) Correlation scores increased when three smaller features were defined in the original feature. Using these smaller features with higher signal-to-noise ratios more than doubled correlation scores.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: OLA scan noise impacts terrain modeling at low altitudes. Noise from OLA measurement limitations drowns out information about smaller terrain features in NFT rendering, resulting in a very low correlation score of 0.296.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: Use of asteroid truth models for ground testing. Each truth model was used to simulate all OCAMS images and OLA scans needed to build the SPC and OLA MLNs. Those MLNs were then used to define NFT feature data. In parallel, each truth model was also used to simulate NavCam images for testing the NFT features.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: Timeline of MLN ground tests for NFT. The box width represents the test duration, with major mission milestones shown along the bottom.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: SPC feature performance vs. altitude. Each line represents performance for a single feature. The five features here correspond to the five features shown in Figure 6.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: Comparison of truth model terrain between Shape 3 and Shape 4. (a) Rugged terrain represented in Shape 3. (b) Smoother terrain in Shape 4, developed to capture the large, smooth landing sites that were originally expected at Bennu. Both images were rendered with a Sun elevation angle of 55°.
Paper: Ground Testing of Digital Terrain Models to Prepare for OSIRIS-REx Autonomous Vision Navigation Using Natural Feature Tracking
Authors: C. E. Mario, C. J. Miller, C. D. Norman, E. E. Palmer, J. Weirich, O. S. Barnouin, M. G. Daly, J. A. Seabrook, D. A. Lorenz, R. D. Olds, R. Gaskell, B. J. Bos, B. Rizk, D. S. Lauretta
Figure caption: SPC Stress Test correlation results. Plots show feature incidence angle vs. (a) correlation score and (b) pixel error for image GSDs 2.5–4 cm pixel−1. Passing correlation scores were greater than 0.6, while passing pixel errors were less than 6 pixels. Each line represents all test results for images at a given GSD, with the line and error bars representing the mean and standard deviation, respectively.
Paper: The SSDC Role in the LICIACube Mission: Data Management and the MATISSE Tool
Authors: Angelo Zinzi, Vincenzo Della Corte, Stavro L. Ivanovski, Alice Lucchetti, Elena Mazzotta Epifani, Federico Miglioretti, Maurizio Pajola, Alessandro Rossi, Olivier Barnouin, Raymond C. Espiritu, Elisabetta Dotto, Marilena Amoroso, Ivano Bertini, John R. Brucato, Andrea Capannolo, Gabriele Cremonese, Biagio Cotugno, Massimo Dall'Ora, Jasinghege D. P. Deshapriya, Valerio Di Tana, Igor Gai, Pedro H. A. Hasselmann, Simone Ieva, Gabriele Impresario, Michèle Lavagna, Andrea Meneghin, Dario Modenini, Davide Perna, Simone Pirrotta, Giovanni Poggiali, Pasquale Palumbo, Emanuele Simioni, Simone Simonetti, Paolo Tortora, Marco Zannoni, Giovanni Zanotti
Figure caption: Data flow and communication of the LICIACube Mission and SOC. Acronyms are as follows: Applied Physics Laboratory (APL), Jet Propulsion Laboratory (JPL), Deep Space Network (DSN), Telemetry (TM), Telecommands (TC), Navigation (NAV), LICIACube (LCC), Attitude and Orbital Control System (AOCS), Attitude Determination & Control Subsystem (ADCS), Propulsion Subsystem (PS), and Telemetry Tracking & Command (TT&C).
Paper: The SSDC Role in the LICIACube Mission: Data Management and the MATISSE Tool
Authors: Angelo Zinzi, Vincenzo Della Corte, Stavro L. Ivanovski, Alice Lucchetti, Elena Mazzotta Epifani, Federico Miglioretti, Maurizio Pajola, Alessandro Rossi, Olivier Barnouin, Raymond C. Espiritu, Elisabetta Dotto, Marilena Amoroso, Ivano Bertini, John R. Brucato, Andrea Capannolo, Gabriele Cremonese, Biagio Cotugno, Massimo Dall'Ora, Jasinghege D. P. Deshapriya, Valerio Di Tana, Igor Gai, Pedro H. A. Hasselmann, Simone Ieva, Gabriele Impresario, Michèle Lavagna, Andrea Meneghin, Dario Modenini, Davide Perna, Simone Pirrotta, Giovanni Poggiali, Pasquale Palumbo, Emanuele Simioni, Simone Simonetti, Paolo Tortora, Marco Zannoni, Giovanni Zanotti
Figure caption: Surface data (i.e., modeled temperature) projected over the 67P comet nucleus shape model as visualized by MATISSE. This image has been generated using observations and models not available to the public and described by Tosi et al. (2019), where more details about it can be found.
Paper: The SSDC Role in the LICIACube Mission: Data Management and the MATISSE Tool
Authors: Angelo Zinzi, Vincenzo Della Corte, Stavro L. Ivanovski, Alice Lucchetti, Elena Mazzotta Epifani, Federico Miglioretti, Maurizio Pajola, Alessandro Rossi, Olivier Barnouin, Raymond C. Espiritu, Elisabetta Dotto, Marilena Amoroso, Ivano Bertini, John R. Brucato, Andrea Capannolo, Gabriele Cremonese, Biagio Cotugno, Massimo Dall'Ora, Jasinghege D. P. Deshapriya, Valerio Di Tana, Igor Gai, Pedro H. A. Hasselmann, Simone Ieva, Gabriele Impresario, Michèle Lavagna, Andrea Meneghin, Dario Modenini, Davide Perna, Simone Pirrotta, Giovanni Poggiali, Pasquale Palumbo, Emanuele Simioni, Simone Simonetti, Paolo Tortora, Marco Zannoni, Giovanni Zanotti
Figure caption: Design of the calibration pipeline.
Paper: The SSDC Role in the LICIACube Mission: Data Management and the MATISSE Tool
Authors: Angelo Zinzi, Vincenzo Della Corte, Stavro L. Ivanovski, Alice Lucchetti, Elena Mazzotta Epifani, Federico Miglioretti, Maurizio Pajola, Alessandro Rossi, Olivier Barnouin, Raymond C. Espiritu, Elisabetta Dotto, Marilena Amoroso, Ivano Bertini, John R. Brucato, Andrea Capannolo, Gabriele Cremonese, Biagio Cotugno, Massimo Dall'Ora, Jasinghege D. P. Deshapriya, Valerio Di Tana, Igor Gai, Pedro H. A. Hasselmann, Simone Ieva, Gabriele Impresario, Michèle Lavagna, Andrea Meneghin, Dario Modenini, Davide Perna, Simone Pirrotta, Giovanni Poggiali, Pasquale Palumbo, Emanuele Simioni, Simone Simonetti, Paolo Tortora, Marco Zannoni, Giovanni Zanotti
Figure caption: LEIA simulated image with spatial resolution corresponding to that expected at LICIACube closest approach.
Paper: The SSDC Role in the LICIACube Mission: Data Management and the MATISSE Tool
Authors: Angelo Zinzi, Vincenzo Della Corte, Stavro L. Ivanovski, Alice Lucchetti, Elena Mazzotta Epifani, Federico Miglioretti, Maurizio Pajola, Alessandro Rossi, Olivier Barnouin, Raymond C. Espiritu, Elisabetta Dotto, Marilena Amoroso, Ivano Bertini, John R. Brucato, Andrea Capannolo, Gabriele Cremonese, Biagio Cotugno, Massimo Dall'Ora, Jasinghege D. P. Deshapriya, Valerio Di Tana, Igor Gai, Pedro H. A. Hasselmann, Simone Ieva, Gabriele Impresario, Michèle Lavagna, Andrea Meneghin, Dario Modenini, Davide Perna, Simone Pirrotta, Giovanni Poggiali, Pasquale Palumbo, Emanuele Simioni, Simone Simonetti, Paolo Tortora, Marco Zannoni, Giovanni Zanotti
Figure caption: Schematic representation of the steps used by MATISSE to search and process data.
Paper: The SSDC Role in the LICIACube Mission: Data Management and the MATISSE Tool
Authors: Angelo Zinzi, Vincenzo Della Corte, Stavro L. Ivanovski, Alice Lucchetti, Elena Mazzotta Epifani, Federico Miglioretti, Maurizio Pajola, Alessandro Rossi, Olivier Barnouin, Raymond C. Espiritu, Elisabetta Dotto, Marilena Amoroso, Ivano Bertini, John R. Brucato, Andrea Capannolo, Gabriele Cremonese, Biagio Cotugno, Massimo Dall'Ora, Jasinghege D. P. Deshapriya, Valerio Di Tana, Igor Gai, Pedro H. A. Hasselmann, Simone Ieva, Gabriele Impresario, Michèle Lavagna, Andrea Meneghin, Dario Modenini, Davide Perna, Simone Pirrotta, Giovanni Poggiali, Pasquale Palumbo, Emanuele Simioni, Simone Simonetti, Paolo Tortora, Marco Zannoni, Giovanni Zanotti
Figure caption: The MATISSE 2.0 homepage, with the map for selecting data.
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: Statistical evolution of the distributions of the five test cases given in Table 2, (175706) 1996 FG3, and (35107) 1991 VH during 500,000 yr. Shown are the standard deviation of semimajor axis, eccentricity, inclination as a function of the number of encounters (top row) and square root of time (middle row), and variation of the mean value over time with respect to the initial value of semimajor axis, eccentricity, and inclination (bottom row).
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: Dispersion in the distributions of the five asteroids in Table 2, (175706) 1996 FG3, and (35107) 1991 VH after 100,000 yr (top) and 500,000 yr (bottom). Shown are semimajor axis vs. eccentricity (left) and semimajor axis vs. inclination (right). Initial uncertainty distributions are detailed in Appendix A and shown in red. See text for the explanation of the resonances found in the semi-analytical propagation.
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: Trajectories of a particle that mirrors the binary asteroid (35107) 1991 VH for 500 yr. Three methods are compared: numerical integration of the heliocentric orbit of the asteroid with two external perturbers in constant sets of elements, Earth and Jupiter (4BP; red); full ephemeris as accessed in HORIZONS (Giorgini & JPL Solar System Dynamics 2021; green); and the semi-analytical propagation method (SA-prop; blue).
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: 500,000 yr Monte Carlo semi-analytical propagation of asteroid (35107) 1991 VH. Initial conditions are given in Table 2 as obtained from HORIZONS (Giorgini & JPL Solar System Dynamics 2021), and uncertainties in the distribution are obtained from JPL's SSD/CNEOS Small-Body DataBase (SSD/CNEOS API Service 2021) as described in Appendix A. Elements shown are perihelion, eccentricity, inclination, argument of the ascending node, argument of perihelion, and MOID. Gray lines show individual simulations, and black lines are the median of the 500 simulations of each parameter shown.
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption:  Semi-analytical propagation of asteroid Cases 1–5, (35107) 1991 VH, and (175706) 1996 FG3 for 500,000 yr. Histograms are at the initial time, after 100,000 yr, and at the final time. Initial conditions are given in Table 2 as obtained from HORIZONS (Giorgini & JPL Solar System Dynamics 2021), and uncertainties in the distribution are obtained from JPL's SSD/CNEOS Small-Body DataBase (SSD/CNEOS API Service 2021) as described in Appendix A.
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: Close encounters in the semi-analytical propagation of the fictitious NEOs Cases 1−3 with initial conditions given in Table 2. Shown is the closest approach distance d CA (au) of the encounters and MOID with the planets. Circles indicate close encounters, and solid lines indicate the MOID. The color-code indicates the planets: Venus (green), Earth (blue), Mars (red).
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: Number of encounters experienced by the five test cases given in Table 2, (175706) 1996 FG3, and (35107) 1991 VH during 500,000 yr. Shown are the mean of the distributions of 500 particles (solid lines) and 1σ bounds (shadowed area).
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: Comparison between the 1000 trajectories obtained using numerical integration (blue) and semi-analytical propagation (orange) of a fictitious population of NEOs after 200,000 yr. The probability density function is shown for the perihelion distance, inclination, and argument of perihelion. The analytical probability density function of the initial conditions is shown as a solid red line. On the right, we show the mean number of encounters found as a function of the closest approach distance for both methods.
Paper: Semi-analytical Near-Earth Objects Propagation: The Orbit History of (35107) 1991 VH and (175706) 1996 FG3
Authors: Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres
Figure caption: Close encounters in the semi-analytical propagation of the fictitious NEO Cases 1−3 with initial conditions given in Table 2. Shown is V ∞ at closest approach of the encounter (km s−1). The color-code indicates the planets: Venus (green), Earth (blue), Mars (red).
Paper: Sputtering Behavior of Rough, Polycrystalline Mercury Analogs
Authors: H. Biber, J. Brötzner, N. Jäggi, P. S. Szabo, J. Pichler, C. Cupak, C. Voith, B. Cserveny, A. Nenning, A. Mutzke, M. V. Moro, D. Primetzhofer, K. Mezger, A. Galli, P. Wurz, F. Aumayr
Figure caption: Experimental geometry: incoming projectile ions are hitting the thin film sample on the QCM or a pressed mineral pellet under an impact angle α with respect to the surface normal. Sputtered particles are registered as a mass increase on the ”catcher” QCM positioned under an angle of β with respect to the surface normal at a distance r  C  = 17 mm from the center of the sample.
Paper: Sputtering Behavior of Rough, Polycrystalline Mercury Analogs
Authors: H. Biber, J. Brötzner, N. Jäggi, P. S. Szabo, J. Pichler, C. Cupak, C. Voith, B. Cserveny, A. Nenning, A. Mutzke, M. V. Moro, D. Primetzhofer, K. Mezger, A. Galli, P. Wurz, F. Aumayr
Figure caption: Comparison between the angular dependence of the sputtered particles for irradiation of the wollastonite pellet (orange squares) and the amorphous thin wollastonite film on a QCM (blue circles) with 2 keV Ar+ ions. Two different angles of ion incidence were probed: α = 45° (left) and α = 60° (right). A fit of the shape ﹩A\cos {\left(\beta -\zeta \right)}^{n}﹩ to SDTrimSP results for trajectories in the same angle as the sensitive catcher area is shown as purple line.
Paper: Sputtering Behavior of Rough, Polycrystalline Mercury Analogs
Authors: H. Biber, J. Brötzner, N. Jäggi, P. S. Szabo, J. Pichler, C. Cupak, C. Voith, B. Cserveny, A. Nenning, A. Mutzke, M. V. Moro, D. Primetzhofer, K. Mezger, A. Galli, P. Wurz, F. Aumayr
Figure caption: Comparison between the angular dependence of the sputtered particles for irradiation of the enstatite pellet (orange squares) and the enstatite thin film (blue circles) with 2 keV Ar+ ions. Two angles of ion incidence were probed: α = 45° (left) and α = 60° (right). A fit of the shape ﹩A\cos {\left(\beta -\zeta \right)}^{n}﹩ to the experimental data and to SDTrimSP results for trajectories in the same angle as the sensitive catcher area is shown as purple line.
Paper: Experimental Constraints on Deliquescence of Calcium Perchlorate Mixed with a Mars Regolith Analog
Authors: Rachel A. Slank, Edgard G. Rivera-Valentín, Vincent F. Chevrier
Figure caption: (a) Mass vs. time (left-hand side and green) and water vapor pressure gradient vs. time (right-hand side and blue) for the experiments that were under conditions that would have permitted deliquescence. At the beginning of all four experiments, the water vapor pressure gradient was positive. After the first hour, though, the gradient was negative. This was maintained for the rest of the experiment. This means that for most of the experiment run time there was more water vapor above the sample than in the atmosphere. The water vapor pressure gradient also increased and stabilized to between 30 and 50 Pa. If the chamber was in equilibrium, it should have stabilized out around 0 Pa. The change in the water vapor pressure was calculated using the RH hygrometer directly above the sample. Small fluctuations in mass (as seen in panel (d)) over time may have been caused by instrumentation, such as the vacuum pump turning on and off.
Paper: Experimental Constraints on Deliquescence of Calcium Perchlorate Mixed with a Mars Regolith Analog
Authors: Rachel A. Slank, Edgard G. Rivera-Valentín, Vincent F. Chevrier
Figure caption: Evidence of deliquescence after Experiment 10 was removed from the chamber and exposed to ambient conditions. (a) Sample directly after the experiment ended and was removed from the Mars simulation chamber. There were no signs of regolith darkening on the surface. (b) Visible wetness on the edge of the petri dish and some regolith darkening buried in the regolith. This is the only location where regolith darkening was observed (c) Wet regolith was observed after the sample was moved to a different petri dish. (d) After 17 minutes, regolith darkening started to occur, as seen by the darker color around certain salt crystals in the upper half of the petri dish. (e) Here ∼40% of the surface salt had deliquesced and had regolith darkening around the salt crystal after 27 minutes. As with Experiment 9, the salts did not seem to deliquesce based on the grain size of the salt.