Chemists have developed a generative AI model that can make it much easier to determine the structures of powdered crystal materials. The prediction model could help researchers characterize materials ...

The new method can determine crystal structures underlying experimental data thus far difficult to analyze. A joint research team led by Yuuki Kubo and Shiji Tsuneyuki of the University of Tokyo has ...

Most solid materials we rely on, from steel, to plastics and ceramics, are designed to have specific properties. Whether a material is soft and flexible, or stiff and tough depends on how molecules ...

The ability to predict crystal structures is a key part of the design of new materials. New research shows that a mathematical algorithm can guarantee to predict the structure of any material just ...

Researchers developed a method that gradually adds and removes atoms in simulations, enabling realistic modeling of crystal defects that affect material strength.

Inorganic crystal materials, for example, may show enormous promise once you first synthesize them, but all this potential could lead nowhere if the crystals don't remain stable; it's no good ...

An artificial intelligence created by Google DeepMind may help revolutionise materials science, providing new ways to make better batteries, solar panels, computer chips and many more vital ...

Researchers at Google DeepMind and Lawrence Berkeley National Laboratory today announced in a stunning scientific breakthrough that they have developed a new AI system called GNoME that has discovered ...

Developing and manufacturing effective, safe, reliable new drugs or critical new materials for use in semiconductors or applications involving dangerous materials requires many layers of knowledge.