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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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This report aims to answer the question: “Will ground penetrating radar (GPR) be able to measure lunar subsurface resources from a 10km or above orbit?” Similarly, “Could a reasonable satellite-based system achieve the radar parameters required for lunar orbital GPR?” This report is not proposing a system but exploring if one is possible.
As NASA strives towards a long duration presence on the Moon, it has become increasingly important to learn how to better utilize resources from the lunar surface for everything from habitats, vehicle infrastructure, and chemical extraction. To that end, a variety of lunar simulants have been sourced from terrestrially available volcanic minerals and glass as Apollo regolith is unavailable for experimentation needing large masses. However, while mineralogy and chemical composition can approach that of lunar material in these simulants, there are still distinct non-lunar phases such as hydrates, carbonates, sulfates, and clays that can cause simulants to behave distinctly non-lunar in a variety of processing conditions that maybe applied in-situ to lunar material. Notably, severe glassy bubbling has been documented in a variety of vacuum sintering experiments on JSC-1A lunar mare simulant heated via microwaves. The origins of this outgassing have not been well understood but are normally attributed to the decomposition of non-lunar contaminates intrinsic to virtually all terrestrially sourced simulants. As such, a series of controlled environmental tests were performed to ascertain the origins of the high temperature outgassing and to develop heat treatments that can drive JSC-1A closer to lunar composition and behavior. It was found that in JSC-1A at elevated temperatures distinct gas evolutions of water, carbon dioxide, and sulfur dioxide occur in both inert gas and vacuum. Additionally, the presence of hydrogen during heat treatments was shown to dramatically change gas evolutions, leading to distinctly more lunar-like composition and behavior from JSC-1A simulant.
The detection and characterization of lunar water are critical for enabling sustainable human and robotic exploration of the Moon. Orbital neutron spectrometers, such as instruments on Lunar Prospector and the Lunar Reconnaissance Orbiter, have revealed hydrogen-rich regions near the poles but are limited by coarse spatial resolution and low counting efficiency. We present a compact, lightweight, and low-power epithermal neutron detector based on boron-coated silicon imagers, designed to probe subsurface hydrogen at decimeter scales from mobile platforms such as lunar rovers. This instrument leverages the high neutron capture cross-section of 10 B to convert epithermal neutrons into detectable α and 7 Li ions in a fully-depleted silicon imager, providing a unique event topology to identify neutrons while suppressing backgrounds. Monte Carlo simulations demonstrate that a 3 μm boron layer achieves optimal neutron detection efficiency, further enhanced with polyethylene moderation to improve sensitivity to the 0.4 eV–500 keV epithermal energy range. For a 10 cm 2 active area, the detector achieves sensitivity to H 2 O weight fractions as low as 0.01 wt% in a 15 minute measurement. This scalable, portable, low-mass design is well-suited for integration into upcoming Artemis and commercial lunar rovers, providing a transformative capability for in-situ resource prospecting and ground-truth validation of orbital measurements.
Microbial biomanufacturing is important to accelerate lunar construction because it can leverage lunar material and waste streams as feedstocks to create a circular production system. In-space bio-mining and biomanufacturing using moon and asteroidal source material will enable the creation of infrastructure, produce industrial fuels and lubricants, and enable recovery of actinides and rare-earth elements (REEs) present in trace concentrations. Moreover, biomanufacturing in closed-loop systems (recycling and reuse of resources toward the establishment of a circular economy) will enable long-term lunar activities by recycling waste (CO 2 , gray water) and producing oxygen and biomaterials. Our response focuses on the use of lunar regolith and waste streams as feedstocks for protein and microbial-enabled biomining and bioprocessing to extract actinides and REEs, and to create biocomposites for lunar infrastructure. We envision an enclosed process that initiates with (1a) extracting actinides and REEs from lunar regolith using immobilized proteins, followed by (1b) creating biocomposites from the post-extracted lunar regolith for infrastructure, and (1c) cultivating diatoms and other microalgae on waste streams to harvest silica shells for incorporating into biocomposites and to generate O 2 for human respiration and/or producing refinable feedstocks. LLNL has significant expertise in all three processes and provides facilities, personnel, and expertise at the intersection of metal (lanthanide, actinide, transition) separations, purifications, biohydrometallurgy, radiobiochemistry, synthetic and systems biology, and materials science and engineering. Importantly, all three processes are relatively well-studied for Earth-based workflows and can be derisked for demonstration on the lunar surface by 2029.
Cislunar space, encompassing the region from geosynchronous orbit to beyond the Moon, is poised to become a cornerstone for future exploration, scientific discovery, and national security. Missions in this region, spanning durations from weeks to decades, require robust infrastructure and reliable transit capabilities. The complex gravitational influences of the Moon, Sun, and planets, along with thermal radiation from Earth and the Sun, lead to significant trajectory deviations, resulting in kilometer-scale errors within days. Leveraging the high-performance computing resources at Lawrence Livermore National Laboratory (LLNL), we have simulated one million high-fidelity cislunar trajectories, now publicly available via LLNL’s Green Data Oasis and the Unified Data Library. Generated using the open-source Space Situational Awareness Python package, these trajectories match the precision of commercial tools such as AGI’s Systems Tool Kit and NASA’s General Mission Analysis Tool. This data set is a valuable resource for reference, statistical analysis of cislunar orbit populations, and training machine learning models for rapid orbit classification with minimal observational input. Preliminary analysis reveals stable bands in Keplerian element space, particularly around five geosynchronous radii across a range of inclinations and eccentricities. Beyond this threshold, the Moon’s influence disrupts most unassisted orbits, though co-orbiting L4/L5 Lunar Trojans persist throughout the six-year simulation.