When scientists study how materials behave under extreme conditions, they typically examine what happens under compression. But what occurs when you pull matter apart in all directions simultaneously?

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.

A new artificial intelligence model can predict how atoms arrange themselves in crystal structures. A new artificial intelligence model that can predict how atoms arrange themselves in crystal ...

Most people associate crystals with semi-transparent stones with therapeutic properties or suncatchers that operate as rainbow prisms. But for scientists and engineers, a crystal is a type of material ...

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 ...

SPaDe-CSP first predicts most probable space groups and crystal densities using machine learning and then employs an efficient neural network potential for structure refinement. Prediction of crystal ...

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 ...

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 ...

Metalworkers and metallurgists have long appreciated the ability to tailor the performance characteristics of steel (an alloy of iron and carbon), including their strength, hardness, ductility and ...