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 setback in growing light-responsive crystals led UB chemist Jason Benedict and his team to a novel method for mapping molecular arrangements.

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 ...

A research team from the Institute of Statistical Mathematics and Panasonic Holdings Corporation has developed a machine learning algorithm, ShotgunCSP, that enables fast and accurate prediction of ...

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 ...

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 ...