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 ...

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 ...

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?

In materials science, if you can understand the "texture" of a material—how its internal patterns form and shift—you can ...

Google DeepMind researchers have discovered 2.2 million crystal structures that open potential progress in fields from renewable energy to advanced computation, and show the power of artificial ...

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 ...

Scientists have redefined the state-of-the-art in modeling and predicting the free energy of crystals. Their work shows that crystal form stability under real-world temperature and humidity conditions ...

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 ...

Removing excess iron reveals FeTe as a superconductor, and its properties can be engineered using layered structures and ...