Hydrogen is a promising fuel for developing sustainable industrial processes, but its use is hindered by hydrogen embrittlement—a phenomenon that weakens metals and can cause sudden failure. Now, researchers from Japan have provided the first experimental evidence linking surface roughness to atomic-scale defects caused by hydrogen in iron. Using positron annihilation lifetime spectroscopy, they showed that rougher surfaces result in greater accumulation of defects, offering new insights into designing hydrogen-resistant materials through precision surface engineering.

A deep blue organic light-emitting diode (OLED) developed by researchers at Science Tokyo operates on just a single 1.5 V, overcoming the high-voltage and color-purity problems that have long limited blue OLEDs. The breakthrough was achieved by introducing a new molecular dopant that prevents charge trapping, a problem that previously hampered the performance of low-voltage OLEDs. The resulting device produces sharp blue emission that meets BT.2020 standards, paving the way toward brighter, more energy-efficient displays.

Sodium-ion batteries (SIBs) are a promising, low-cost alternative to lithium-ion batteries for both personal electronics and large-scale energy storage, but their adoption is limited by their poor stability in air and water. In a recent study, researchers from Japan addressed this challenge by doping the SIB cathode material Na_2/3[Fe_1/2Mn_1/2]O₂ with calcium. This simple modification greatly improved stability and performance, paving the way for more practical and sustainable battery technologies.

Scientists at City University of Hong Kong have cracked the code to identify ‘passwords’ needed to unlock the full potential of CRISPR, the revolutionary gene-editing "molecular scalpel" that can fix genetic diseases.

A multicenter study led by Prof. Shuixing Zhang and Prof. Bin Zhang from the First Affiliated Hospital of Jinan University enrolled 246 patients with locally advanced NPC treated with immunotherapy. By applying artificial intelligence algorithms, the team extracted and selected optimal radiomic features from medical imaging to construct a predictive model.