Astroparticle physics: Neutrinos weigh less than 0.45 electronvolts
Peer-Reviewed Publication
Updates every hour. Last Updated: 7-Oct-2025 05:11 ET (7-Oct-2025 09:11 GMT/UTC)
The international KArlsruhe TRItium Neutrino Experiment (KATRIN) at the Karlsruhe Institute of Technology (KIT) has once again surpassed its own achievements. The latest data establish an upper limit of 0.45 eV/c2 (equivalent to 8 x 10-37 kilograms) for the neutrino mass. With this result, KATRIN, which measures neutrino mass in the laboratory using a model-independent method, has once again set a world record. The researchers have published their results in the journal Science (DOI: 10.1126/science.adq9592).
In a striking demonstration of molecular control, a team of Japanese scientists has harnessed light to reverse the twist in self-assembling molecules. The study led by Professor Shiki Yagai from Chiba University identifies how trace residual aggregates in photo-responsive azobenzene solutions can reverse helical chirality through secondary nucleation. By using precise control of ultraviolet and visible light, the researchers could switch between the rotation of helices, offering a breakthrough for novel materials with tunable properties.
A research team has developed a groundbreaking two-dimensional (2D) phase-transition memristor leveraging intrinsic ion migration for ultra-low power consumption and high endurance. Unlike conventional memristors that suffer from crystal damage and high energy demands, the newly developed Intrinsic Ion Migration (IIM) memristor eliminates the need for external ion intercalation. This innovative approach results in an unprecedented SET power consumption of just 1 μW at 100 mV and an ultrafast switching speed of 80 ns, positioning it as a promising candidate for next-generation neuromorphic computing and in-memory processing.
A new publication from Opto-Electronic Advances; 10.29026/oea.2025.240207, discusses how light boosts exciton transport in organic molecular crystal.
A new publication from Opto-Electronic Advances; DOI 10.29026/oea.2025.240189, discusses enhanced photoacoustic microscopy with physics-embedded degeneration learning.