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.

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 ...

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 ...

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 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 ...

Crystal structure prediction (CSP) is typically addressed by combining first-principles calculations with optimization algorithms. For example, genetic algorithms are often employed to iteratively ...

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 ...