Naked photo-bombing comet found in public image
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Updates every hour. Last Updated: 21-Oct-2026 07:16 ET (21-Oct-2026 11:16 GMT/UTC)
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.
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.