When a star reaches its final stages of life, it ends in a bright and powerful explosion called a supernova and scatters material across the universe. A new study led by a University of Hawai‘i at Mānoa researcher discovered that the Moon’s mixed-up soil can be read as a cosmic time capsule for exploding stars.

At nearly 240,000 miles from Earth, the moon is getting its first spaceport, Gateway — and engineers developed the mathematical flight manual and orbital “rules of the road” for multiple spacecraft to safely share one of the most challenging environments ever considered for human exploration.

What happens to a space rock as it falls through Earth’s atmosphere and becomes a meteorite? By studying 75 meteorite falls captured on video and in photographs, researchers identified seven distinct phases in the journey from space rock to meteorite. Their findings show that melting and fragmentation, rather than simply evaporation and "burning up", control how a rock loses mass, slows down and ultimately reaches the ground. The journal Meteoritics & Planetary Science published these findings.

"We used to think that solid rocks would evaporate from the enormous heat and brilliant light generated in the air collision," said meteor astronomer and lead author Dr. Peter Jenniskens of the SETI Institute and NASA Ames Research Center. "We found instead that first melting and then fragmentation controls how a rock loses mass."

The team found that a fireball goes through seven stages as it moves through Earth’s atmosphere. Each stage is shaped by different physical processes.

Researchers at UCSB and UT Austin describe the violent event that have shot a super-massive black hole into intergalactic space.

Two Southwest Research Institute-developed technologies have been selected as winners of prestigious R&D 100 Awards. R&D World recognized SwRI’s patented Parallelogram Synchronized Truss Assembly (PaSTA) technology and the Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS), developed in collaboration with the U.S. Department of Energy’s (DOE’s) National Laboratory of the Rockies (NLR), as two of the most important innovations of 2026.

Plastic might be the last ingredient you would ever add to a cookie recipe. But a team of researchers is looking to change that. They’ve programmed yeasts to turn plastic and agricultural waste into edible proteins and flavoring molecules, creating a treat from trash. The technology not only offers a new upcycling method, but could also sustain life in disaster zones or manned deep-space missions. The researchers will present their results at ACS Fall 2026.

Plasma bubbles in the ionosphere over equatorial and low-latitude regions are a common nighttime plasma density depletion structure that can cause severe scintillation interference on high-frequency communications, making them an important target of space weather monitoring. Traditional detection methods rely on statistical thresholds derived from temporal fluctuations in ion density; however, plasma bubbles exhibit significant variability in spatiotemporal scales (ranging from kilometers to hundreds of kilometers), and their occurrence frequency is strongly modulated by solar activity and seasonal factors. Consequently, fixed-threshold methods struggle to accommodate this diversity, with miss rates reaching up to 40% during periods of low solar activity. Although deep learning has demonstrated powerful capabilities in automatically extracting and recognizing complex waveform features in fields such as medical image segmentation and signal peak detection, its systematic application to ionospheric plasma bubble detection—and thus addressing the adaptability deficiencies of traditional threshold methods—remains underexplored.

With growing concerns over the impact threat of near-Earth small bodies and the utilization of space resources, the orbital evolution of binary asteroid systems has become an important subject in space science. When describing the full two-body dynamics of such systems, the gravitational potential of irregular bodies is determined by both their positions and attitudes, leading to coupling between translational and rotational motions, and the resulting model complexity significantly exceeds that of the classical two-body problem. Although existing numerical methods, such as explicit Runge–Kutta integrators, are widely used, they fail to preserve the symplectic structure and Lie group geometric properties of the system. In long-term simulations, key conserved quantities such as total energy and angular momentum are prone to numerical drift, severely undermining the long-term credibility of orbital predictions. While Lie group variational integrators can preserve geometric structure to a certain extent, their implicit equations are formulated on Lie group elements, which incurs substantial computational overhead. Therefore, how to construct a high-performance integration method that simultaneously achieves numerical accuracy, structure preservation, and computational efficiency has become a core challenge in the long-term evolutionary simulation of binary asteroid systems.