The presence of frozen volatiles (especially H2O ice) has been proposed in the permanently shadowed regions (PSRs) near the poles of the Moon, based on various remote measurements including the visible and near-infrared (VNIR) spectroscopy. Compared with the middle- and low-latitude areas, the VNIR spectral signals in the PSRs are noisy due to poor solar illumination. Coupled with the lunar regolith coverage and mixing effects, the available VNIR spectral characteristics for the identification of H2O ice in the PSRs are limited. Deep learning models, as emerging techniques in lunar exploration, are able to learn spectral features and patterns, and discover complex spectral patterns and nonlinear relationships from large datasets, enabling them applicable on lunar hyperspectral remote sensing data and H2O-ice identification task. Here we present H2O ice identification results by a deep learning-based model named one-dimensional convolutional autoencoder. During the model application, there are intrinsic differences between the remote sensing spectra obtained by the orbital spectrometers and the laboratory spectra acquired by state-of-the-art instruments. To address the challenges of limited training data and the difficulty of matching laboratory and remote sensing spectra, we introduce self-supervised learning method to achieve pixel-level identification and mapping of H2O ice in the lunar south polar region. Our model is applied to the level 2 reflectance data of Moon Mineralogy Mapper. The spectra of the identified H2O ice-bearing pixels were extracted to perform dual validation using spectral angle mapping and peak clustering methods, further confirming the identification of most pixels containing H2O ice. The spectral characteristics of H2O ice in the lunar south polar region related to the crystal structure, grain size, and mixing effect of H2O ice are also discussed. H2O ice in the lunar south polar region tends to exist in the form of smaller particles (similar to 70 mu m in size), while the weak/absent 2-mu m absorption indicate the existence of unusually large particles. Crystalline ice is the main phase responsible for the identified spectra of ice-bearing surface however the possibility of amorphous H2O ice beneath optically sensed depth cannot be ruled out.

The paper presents new radar maps of the south polar region of the Moon at 4.2 cm wavelength with an average spatial resolution of 90 m. The maps are based on radar images obtained in 2023 using the 64-m TNA-1500 antenna of the Bear Lakes Satellite Communications Center of the Special Design Bureau of the Moscow Power Engineering Institute and the 13.2-m RT-13 radio telescopes at the Svetloe and Zelenchukskaya observatories of the Institute of Applied Astronomy of the Russian Academy of Sciences. Radar images are formed in a specific coordinate system relating the Doppler frequency shift with the propagation time delay of the echo components, which makes it difficult to tie them to selenographic coordinates. In this paper, an original method for converting echo Doppler frequency and time delay to selenographic latitude and longitude is proposed, using bilinear interpolation by ephemeris nodal values, taking into account long integration times. The accuracy of the reference of the maps constructed in this way was assessed and compared with the LROC WAC global optical map of the Moon and mosaics of permanently shadowed regions from LROC NAC. It is shown that radar maps at 4.2 cm wavelength contain features of the lunar surface that are hidden in optical images and are located in the regolith at depths of up to 1 m or in permanently shadowed regions of the south polar region of the Moon. The maps of the lunar echoes specular and diffuse polarization components, as well as a map of the distribution of circular polarization ratios, are available on the Internet at http://luna.iaaras.ru/ and can be useful for studying the geological history of the Moon, searching for ice deposits, and selecting safe landing sites when planning future lunar missions.

The contributions of external and internal hydration (OH and H2O) on the shape and strength of hydration related features at 3 and 6 mu m for lunar relevant nominally anhydrous minerals were investigated under vacuum conditions. Understanding the effect of hydration on the reflectance spectra of lunar analog materials in the laboratory can provide insights into remote sensing observations of the lunar surface and the potential for 3 and/or 6 mu m observations to determine the speciation of hydration on the Moon. We demonstrate changes in the shape and strength of the broad 3 mu m absorption feature in olivine and anorthite that is associated with the removal of hydration under changing environmental conditions. The overlapping nature of OH and H2O related absorption features in the similar to 3 mu m region makes it difficult to uniquely determine the speciation of hydration. Despite evidence of H2O loss in the 3 mu m region, we do not observe the fundamental bending mode of H2O at 6 mu m, posing potential challenges for the detection H2O on the lunar surface and throughout our solar system.

The MAJIS (Moons And Jupiter Imaging Spectrometer) instrument, part of the JUICE (JUpiter ICy moons Explorer) mission, is a crucial tool for investigating the composition and dynamics of Jupiter's atmosphere, and the surfaces and exospheres of its icy moons. To optimize observational planning and assess instrument performance, we have developed a radiometric simulator that accurately models MAJIS expected signal from various Jovian system targets. This simulator incorporates instrumental parameters, the spacecraft trajectory, observational constraints, and Jupiter's radiation environment. It provides essential outputs, including Signal-to-Noise Ratio (SNR) predictions and optimized instrument settings for different observational scenarios. By simulating both radiometric performance and de-spiking strategies to mitigate the impact of Jupiter radiation belt, the tool aids in refining observation strategies throughout the MAJIS operations. Several scientific applications demonstrate the simulator capabilities, from mapping the surfaces of Ganymede and Europa to detecting exospheric emissions and atmospheric composition on Jupiter. This simulator is a critical asset for maximizing MAJIS scientific return and ensuring optimal data acquisition during MAJIS exploration of the Jovian system. Study cases are presented for illustrating the capability of the simulator to model scenarios such as high-resolution mapping of Ganymede, exosphere characterization and hotspot detection on Io and Europa. These simulations confirm the potential of MAJIS for detecting key spectral features with high signal to noise ratio so as to provide major contributions to the main goals of the mission: habitability and compositional diversity in the Jovian system.

The Moon encountered an extreme space weather event (NOAA G5 class) on 10 May 2024, caused by a series of coronal mass ejections (CMEs). Chandra's Atmospheric Composition Explorer-2 (CHACE-2), a neutral gas mass spectrometer on board Chandrayaan-2 orbiter, made in situ observations of the lunar exosphere during this period. Observations show an increase in total pressure around the arrival time of the CME impact on the Moon. The corresponding total number densities derived from these observations show an enhancement in the total number densities by more than an order of magnitude. The increase in lunar exospheric number densities by a factor > 10, due to the solar wind ion sputter process, is consistent with earlier theoretical modeling. This is the first observational confirmation of the enhancement in lunar exospheric densities during a CME impact.

Lunar soil-based polymers, created using lunar soil as a precursor combined with highly automated 3D printing construction methods, hold great potential for lunar base construction. However, technical challenges such as ambiguities in characterizing rheological behavior and difficulties in regulation limit their 3D printing workability. To address these issues, the applicability of the Bingham model, Herschel-Bulkley (H-B) model, and a modified Bingham model to TJ-1 simulated lunar soil-based polymer was investigated by analyzing the fluidity variation. The effects of the solid-liquid ratio, Ca(OH)2, and Hydroxypropyl Methyl Cellulose ether (HPMC) on the 3D printing performance of the simulated lunar soil-based polymer were explored through one-way tests and standard deviation analysis. The results show that the modified Bingham model more accurately describes the rheological properties of TJ-1 simulated lunar soil-based polymer. HPMC proved to be an effective thixotropic agent for adjusting the 3D printing performance of the polymer. The yield stress and plastic viscosity of the polymer doped with 0.15 % HPMC were 3.577 Pa and 0.733 Pa s, respectively, meeting the requirements for printability. The yield stress and plastic viscosity of the simulated lunar soil polymers ranged from 1.84 to 3.58 Pa and 0.23-0.73 Pa s, respectively. Moreover, the compressive and flexural strengths of the simulated lunar soil polymers were significantly improved by adding Ca(OH)2. The optimal ratios for 3Dprinted simulated lunar soil polymers are a water-cement ratio of 0.30, 10 % NaOH, 8 % Na2SiO3, 6 % Ca(OH)2, and 0.10 % HPMC. Under these conditions, the 28-day compressive strength and flexural strength were 19.5 MPa and 6.9 MPa, respectively, meeting the strength standards of ordinary sintered bricks.The research results could provide a theoretical basis for the subsequent optimization of the simulated lunar soil base polymer mixing ratios for 3D printing.

The extent of moderately volatile elements (MVE) depletion and its effects on the Moon's evolutionary history remain contentious, partly due to unintentionally biased sampling by the Apollo missions from the Procellarum KREEP Terrane. In this study, we analyzed the Zn and K isotope compositions of a series of lunar basaltic meteorites, which vary in Th content and are likely to represent a broader sampling range than previous studies, including samples from the far side of the Moon. Our findings indicate remarkably consistent Zn and K isotope compositions across all lunar basalt types, despite significant variations in Th content. This consistency suggests a relatively homogeneous isotopic composition of volatile elements within the Moon, unaffected by subsequent impact events that formed major basins. Our results suggest that the estimates of MVE abundance and isotopic compositions from the Apollo returned samples are likely representative of the bulk Moon, supporting a globally volatile-depleted lunar interior.

Previous models of microbial survival on the moon do not directly consider the permanently shadowed regions (PSRs). These regions shield their interiors from many of the biocidal factors encountered in space flight, such as UV irradiation and high temperatures, and this shielding reduces the rate at which microbial spores become nonviable. We applied the Lunar Microbial Survival Model (LMS, Schuerger et al., 2019) to the environment found inside PSRs at two craters targeted for exploration by the Artemis missions, Shackleton and Faustini. The model produced rates of reduction of -0.0815 and -0.0683 logs per lunation, respectively, which implies that it would take 30.0 years for Shackleton and 30.8 years for Faustini to accumulate a single Sterility Assurance Level of -12 logs of reduction. The lunar PSRs are therefore one of the least biocidal environments in the solar system and would preserve viable terrestrial microbial contamination for decades.

Although water ice has been detected by satellite observations near the lunar poles, it is unknown if this ice is simply frost on the Moon's surface or if larger ice deposits exist in the subsurface. If ice is present within the subsurface, it is unknown if this ice exists as loose ice grains or as a cement that binds regolith grains together. To create an economically viable extraction and production plan for lunar water ice resources, we must characterize near-surface ice concentration and distribution at small (<10 m) spatial and depth scales. Geophysical methods that can be deployed on the Moon's surface, such as seismic surveying, could supply some of this information for future lunar mine planning. To improve our understanding of how seismic surveying may detect and characterize subsurface lunar ice, we performed laboratory ultrasonic velocity measurements of lunar regolith simulant with variable amounts of granular and cementing ice. These measurements were performed under variable confining pressure (0.005-0.08 MPa) and constant low temperature (-26 degrees C). We used these measurements to calibrate a rock physics model to predict seismic velocity as a function of porosity, pressure, ice concentration and ice texture. Our results show that seismic velocity increases with ice concentration, and this increase is roughly 20 times higher for cementing ice than for granular ice. Our model can be used in future studies to predict how effective seismic methods may be for detecting and characterizing subsurface lunar ice deposits with varying ice properties and geologic complexity.

The abundances and isotopic signatures of volatile elements provide critical information for understanding the delivery of water and other essential life-giving compounds to planets. It has been demonstrated that the Moon is depleted in moderately volatile elements (MVE), such as Zn, Cl, S, K and Rb, relative to the Earth. The isotopic compositions of these MVE in lunar rocks suggest loss of volatile elements during the formation of the Moon, as well as their modification during later differentiation and impact processes. Due to its moderately volatile and strongly chalcophile behaviour, copper (Cu) provides a distinct record of planetary accretion and differentiation processes relative to Cl, Rb, Zn or K. Here we present Cu isotopic compositions of Apollo 11, 12, 14 and 15 mare basalts and lunar basaltic meteorites, which range from delta 65Cu of +0.55 +/- 0.01 %o to +3.94 +/- 0.04 %o (per mil deviation of the 65Cu/63Cu from the NIST SRM 976 standard), independent of mare basalt Ti content. The delta 65Cu values of the basalts are negatively correlated with their Cu contents, which is interpreted as evidence for volatile loss upon mare basalt emplacement, plausibly related to the presence Cl- and S-bearing ligands in the vapour phase. This relationship can be used to determine the Cu isotopic composition of the lunar mantle to a delta 65Cu of +0.57 +/- 0.15 %o. The bulk silicate Moon (BSM) is 0.5%o heavier than the bulk silicate Earth (+0.07 +/- 0.10 %o) or chondritic materials (from -1.45 +/- 0.08 %o to 0.07 +/- 0.06 %o). Owing to the ineffectiveness of sulfide segregation and lunar core formation in inducing Cu isotopic fractionation, the isotopic difference between the Moon and the Earth is attributed to volatile loss during the Moon-forming event, which must have occurred at- or nearequilibrium.