An NJIT-led undergraduate team brought a new idea to NASA — power life-support systems on a lunar base with a swarm of solar-harvesting robots from space.

NASA’s Perseverance rover reveals groundwater, lake water and hydrothermal activity preserved in rocks along Jezero Crater’s Margin Unit in Purdue-led study

Apophis will make an extremely close flyby of Earth on April 13, 2029, at a distance of approximately 31,029 km—an event unprecedented for an asteroid of this size—providing a valuable natural experiment for studying tidal interactions, spin-state variations, and surface material migration between the asteroid and Earth. A large number of ground-based observations and space missions are expected to participate, but most observations will be concentrated from Earth's perspective, leaving observational blind spots as Apophis rapidly recedes from Earth's view after the flyby. LUMIO (Lunar Meteoroid Impacts Observer) is a 12U CubeSat of the European Space Agency, planned to be deployed in a quasi-halo orbit around the Earth–Moon L2 point; its primary mission is to observe meteoroid impact flashes on the lunar farside, with a launch expected in 2028. However, three critical questions remain unanswered: whether LUMIO-Cam—a camera designed for observing impact flashes—can detect Apophis as a sub-pixel target, whether it can resolve fluctuations in its light curve, and whether it can observe for a sufficiently long duration to obtain complete spin-period information.

With the widespread application of space traveling wave tube amplifiers (TWTAs) as core final-stage amplification devices in satellite communication systems, their operational reliability directly affects satellite signal transmission capability, and any failure may even lead to service interruption. Currently, fault statistics for space TWTAs are recorded in text form, encompassing a large number of fault phenomena, causes, and corresponding solutions. However, as the volume of fault events continues to grow, traditional analysis methods relying on manual statistics and empirical judgment suffer from low efficiency and lack of knowledge reasoning capabilities, making it difficult to comprehensively analyze multi-dimensional fault information. Although artificial intelligence technologies, particularly knowledge graphs (KGs) and large language models (LLMs), have demonstrated substantial potential in fault diagnosis, research on effectively integrating these two approaches and applying them to the specific fault diagnosis of space TWTAs remains unexplored. Therefore, how to construct an intelligent diagnosis framework capable of automatically understanding natural language fault descriptions and performing knowledge reasoning has become a key challenge in improving the troubleshooting efficiency and decision support capabilities for space TWTAs.

A new University of Utah-led survey with the Hubble Space Telescope is shedding light on the stellar astrophysics operating in early galaxies. The Treasury of Extremely Metal-Poor O Stars survey uses UV observations from Hubble’s Cosmic Origins Spectrograph to study massive stars in nearby galaxies that are the best available analogs of stars in the early universe. The unprecedently large dataset from TEMPOS could help astronomers build better models of massive stars to understand how they shaped galaxies when the universe was young. Such models are essential to interpret observations of early galaxies now coming from the James Webb Space Telescope.

With the continuously increasing demands on imaging accuracy and on-orbit service life of space optical remote sensors, efficient thermal management under extreme thermal environments has become a critical bottleneck constraining their performance. The substantial temperature fluctuations induced by solar radiation and cold space can cause thermal deformation of optical components, elevation of focal-plane dark current, and even system failure. Traditional metallic thermal conductive materials can no longer meet the increasingly stringent requirements for heat dissipation and lightweighting. Carbon-based materials—including graphene, carbon nanotubes, and carbon/carbon composites—exhibit enormous potential for breaking through the bottlenecks of space thermal management by virtue of their ultra-high thermal conductivity, low density, and low coefficient of thermal expansion. However, systematic performance comparisons and application guidelines for these materials in the specific scenarios of space optical remote sensors remain absent, hindering the effective translation from laboratory research to engineering implementation. Therefore, a systematic review of the thermal conduction mechanisms, fabrication processes, and space applicability of carbon-based high-thermal-conductivity materials is of great significance for promoting their precise application in the thermal management of space optical remote sensors.

With the increasingly prominent role of high-resolution remote sensing data in supporting the digital economy and intelligent industries, on-orbit assembly of large space optical systems has become a critical pathway to overcome launch vehicle constraints and achieve large-aperture detection. However, during on-orbit assembly, the manipulator is required to simultaneously satisfy multiple objectives, including replicating standardized paths, avoiding non-cooperative obstacles, and precisely passing through key waypoints. Existing global methods are limited by the real-time bottleneck of high-dimensional search, while local methods lack global consistency guarantees. Although Dynamic Movement Primitives (DMPs) possess parametric trajectory representation capabilities, they struggle to reconcile the inherent conflict between path shape accuracy and safe obstacle avoidance under multi-objective constraints. Therefore, how to synergistically optimize path passing accuracy and obstacle avoidance safety for manipulators in dynamic, unstructured space environments has become a core challenge constraining the effectiveness of on-orbit autonomous assembly for large-aperture optical systems.