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

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?

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 ...

Using artificial intelligence to create new things is all the rage right now. Whether you want text, computer code, or images, there are uncountable generative AI models that can oblige. Google ...

Condensed-matter physics and materials science have a silo problem. Although researchers in these fields have access to vast amounts of data – from experimental records of crystal structures and ...

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 ...

Duplicates of crystal structures are flooding databases, implicating repositories hosting organic, inorganic, and computer-generated crystals. The issue raises questions about curation practices at ...

Researchers at Google DeepMind and Lawrence Berkeley National Laboratory today announced in a stunning scientific breakthrough that they have developed a new AI system called GNoME that has discovered ...

“Reactive Noble-Gas Compounds Explored by 3D Electron Diffraction: XeF 2 −MnF 4 Adducts and a Facile Sample Handling Procedure” Since Bartlett’s discovery, which is commemorated with an International ...