One of the key steps in developing new materials is “property identification,” which has long relied on massive amounts of experimental data and expensive equipment, limiting research efficiency. A KAIST research team has introduced a new technique that combines “physical laws,” which govern deformation and interaction of materials and energy, with artificial intelligence. This approach allows for rapid exploration of new materials even under data-scarce conditions and provides a foundation for accelerating design and verification across multiple engineering fields, including materials, mechanics, energy, and electronics.

KAIST (President Kwang Hyung Lee) announced on the 2nd of October that Professor Seunghwa Ryu’s research group in the Department of Mechanical Engineering, in collaboration with Professor Jae Hyuk Lim’s group at Kyung Hee University (President Jinsang Kim) and Dr. Byungki Ryu at the Korea Electrotechnology Research Institute (President Namkyun Kim), proposed a new method that can accurately determine material properties with only limited data. The method uses Physics-Informed Machine Learning (PIML), which directly incorporates physical laws into the AI learning process.

Researchers at University of Tsukuba and The University of Tokyo have discovered that radio waves emitted from primordial hydrogen gas in the early Universe contain a "fingerprint" that reveals the properties of dark matter. Theoretical calculations have accurately reproduced the distribution of dark matter and the state of hydrogen gas in the early Universe. Radio observatories planned for construction on the Moon are expected to detect these signals, advancing our understanding of the true nature of dark matter.

Researchers have uncovered how dissolved biochar—tiny carbon particles derived from burning plant material—affects soil nematodes, shedding light on both benefits and risks to these important ecosystem players. The study focused on the common laboratory worm, Caenorhabditis elegans, revealing that the impact of dissolved biochar strongly depends on the amount present in the environment.

MIT researchers found that subtle chemical patterns persist in conventionally manufactured metal alloys, despite the mixing involved. The surprising finding could be used to tune metallic properties for aerospace, energy, and more.