Astronomers using the European Space Agency’s XMM-Newton space observatory and the LOFAR telescope have definitively spotted an explosive burst of material thrown out into space by another star – a burst powerful enough to strip away the atmosphere of any unlucky planet in its path.

A research team at Hosei University and the University of Tokyo has achieved the world’s first stable production of edamame in an artificial light-type plant factory. Using the NFT hydroponic method, yields surpassed open-field cultivation while enhancing sugar and isoflavone content. This breakthrough enables year-round production of high-quality, nutritious edamame in diverse environments from urban buildings to deserts and even outer space, marking a significant step toward sustainable food systems and healthier diets.

Astronomers have uncovered a previously unknown, extreme kind of star factory by taking the temperature of a distant galaxy using the ALMA telescope. The galaxy is glowing intensely in superheated cosmic dust while forming stars 180 times faster than our own Milky Way. The discovery indicates how galaxies could have grown quickly when the universe was very young, solving a long-standing puzzle for astronomers. 

The first generations of stars formed under conditions very different from anywhere we can see in the nearby universe today. Astronomers are studying these differences using powerful telescopes that can detect galaxies so far away their light has taken billions of years to reach us.  

Now, an international team of astronomers led by Tom Bakx at Chalmers University of Technology in Sweden has measured the temperature of one of the most distant known star factories. The galaxy, known as Y1, is so far away that its light has taken over 13 billion years to reach us.  

X-ray absorption spectroscopy (XAS) provides valuable information about a material’s properties and electronic states. However, it requires extensive expertise and manual effort for conventional analysis. Now, researchers from Japan have developed a novel artificial intelligence-based approach for analyzing XAS data that can enable rapid, autonomous, and object material identification. This novel approach outperforms the previous studies in terms of higher accuracy, accelerating the development of new materials.

Crystalline-amorphous composites comprise crystalline grains separated by amorphous boundaries. The combined role of grain size (D) and amorphous boundary thickness (l) on material properties has not been explored. Now, writing in National Science Review, a team from the Hong Kong University of Science and Technology reports simulation results of mechanical properties across the (D, l) parameter space. They identify optimal (D, l) values that provide maximum strength while also enhancing ductility, successfully circumventing the classic strength-ductility tradeoff.