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.

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 ...

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 ...

“Crystal Math” uses equations—and minimal resources—to rapidly predict the 3D structures of molecular crystals, which could speed up R&D for drugs and electronic devices Researchers at New York ...

BUFFALO, N.Y. — University at Buffalo chemist Jason Benedict and his team spent years developing photoswitchable crystals. Every crystal’s shape is a mirror of the internal arrangement of their ...