An international team of physicists has achieved unprecedented accuracy in computing the magnetic properties of the muon using several supercomputers including Europe’s first exascale machine JUPITER. The result, published in Nature, resolves long-standing uncertainty between theory and experiment.

A new paper in Nature Chemistry describes a molecular material that combines a stable internal magnetic structure with almost no external magnetic field. This could prove relevant for energy‑efficient electronics and spintronics.

Just as wave-like patterns can appear on computer screen when pixels do not align, new research led by Flinders University is investigating atomic-scale ‘moiré patterns’ in the promising field of ferroelectricity.

The new study, with experts at Monash University and Nanyang Technological University in Singapore, seeks inroads into electrical and optical science by exploring these complex ‘superlattice’ patterns in various ways to create new energy and material capabilities.

Harnessing the power of generative AI, researchers at Tsinghua University have developed AIGP—a diffusion-based generative framework that enables instant translation of optical properties into fabrication-ready metasurfaces. By using transmission, phase, and polarization as “prompts,” AIGP directly maps optical properties to subwavelength, fabricable structures, generating high-fidelity metasurface designs in seconds. This breakthrough overcomes critical bottlenecks in photonic inverse design and paves the way for large-scale, AI-driven generative optical devices.