A joint research team that included members from Tohoku University has unveiled a new topological insulator (TI), a unique state of matter that differs from conventional metals, insulators, and semiconductors.
Researchers at University of Tsukuba have developed an ultrafast time-resolved scanning electron microscopy instrument by integrating a scanning electron microscope with a femtosecond laser. This innovative system facilitates ...
When stars collapse, they can leave behind incredibly dense but relatively small and cold remnants called neutron stars. If two stars collapse in close proximity, the leftover binary neutron stars spiral in and eventually ...
Entropy is a hot mess. Randomness and disorder are not exactly virtues in science. Yet it turns out, a sloppy jumble of differently sized atoms can do a better job stabilizing certain nanocrystals than a tidy arrangement ...
A research group from University of Tsukuba has discovered that fluctuations of electron spins in magnetic materials trigger a large anomalous Hall effect during phase transition known as the devil's staircase magnetic transition.
While investigating how string theory can be used to explain certain physical phenomena, scientists at the Indian Institute of Science (IISc) have stumbled upon on a new series representation for the irrational number π. ...
Researchers from Skoltech, Jilin University and Beijing HPSTAR in China, and their German colleagues have synthesized and studied a new type of hydrogen-rich superconductor. Technically referred to as an A15-type lanthanum ...
A research team has utilized solid-state spin quantum sensors to scrutinize exotic spin-spin-velocity-dependent interactions (SSIVDs) at short force ranges, reporting new experimental results between electron spins. Their ...
Achieving stability poses a significant challenge in the practical implementation of photoelectrochemical (PEC) water splitting. The main factors affecting the long-term stability of PEC devices are chemical- and photo-corrosion ...
The use of AI to streamline drug discovery is exploding. Researchers are deploying machine-learning models to help them identify molecules, among billions of options, that might have the properties they are seeking to develop ...
