NEWSROOM

New imaging technique visualizes and measures plasmonic waves in device structures designed for practical uses

Researchers at OIST and Hiroshima University have shown that a small magnetic field switches the graphene-like quantum material CeTe₃ between competing electronic patterns — striped and checkerboard. Scanning tunneling microscopy revealed the transformation near absolute zero, driven by electronic frustration coupled to magnetism. The findings, published in Nature Communications, offer a new strategy for controlling collective electronic states in quantum materials with poten

Max Planck researchers have developed a bottom-up method to synthesize nanodiamonds with precisely tailored size and properties. Using molecularly defined nanographene precursors, the team converted flat carbon structures into highly crystalline diamond nanoparticles under high pressure and temperature. This produces purer, more uniform particles (3–4 nm) with incorporated color centers in a single step. The breakthrough advances quantum sensing, single-photon sources, and bi

certain wavelength and direction will also emit heat in the same ways. This fundamental relationship, known as reciprocity, limits our ability to independently control heat absorption and heat emission. But if absorption and emission could be separated, engineers could design devices that absorb heat from one direction while emitting it in another. By ‘steering’ thermal energy, they could create more efficient thermal management, energy conversion, infrared sensing, and th

MIT researchers have found that rhombohedral graphene — a naturally occurring staircase-like stack of four or five atomically thin carbon layers found in ordinary graphite — can host multiple distinct superconducting states simultaneously, a rarity among known superconductors. Publishing in Nature, the team reports that three of these states not only survive exposure to magnetic fields up to around 9 tesla (roughly 180,000 times Earth's magnetic field), which would normally d

MIT researchers have developed a new approach that dramatically improves the modeling of chemically disordered metal alloys, a long-standing challenge in materials science. Traditional simulation techniques struggle with the complex atomic arrangements in real-world alloys. The team addressed this by creating smarter training datasets for machine-learning models that better capture the diverse local chemical environments in disordered materials. Using information theory to ge