The performance of rechargeable batteries is governed by processes deep within their components. A fundamental understanding of electrochemistry, structure–property–performance relationships and the ...

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 ...

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 ...

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?

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 ...

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 ...

Despite being riddled with impurities and defects, solution-processed lead-halide perovskites are surprisingly efficient at ...

What is X-Ray Crystallography? X-ray crystallography is a powerful analytical technique used to determine the atomic and molecular structure of crystalline materials. It involves directing a beam of X ...

MXenes are an emerging class of two-dimensional materials whose properties depend sensitively on the atoms bound to their surfaces. A new synthesis approach now allows researchers to control these ...