Chemists at Yokohama National University combined competition experiments, 3D electronic data and machine learning to predict ...

Researchers developed a machine-learning model that can predict the structures of transition states of chemical reactions in less than a second, with high accuracy. Their model could make it easier ...

Their new model could be used to help chemists design new reactions and catalysts to generate useful products like fuels or drugs, or to model naturally occurring chemical reactions such as those that ...

Scientists used artificial intelligence to uncover nearly 10,000 chemical reactions involved in transforming carbon dioxide ...

A team of researchers at the Indian Institute of Science (IISc) has developed a computational framework that successfully mapped a staggering 9,389 chemical reactions involved in CO₂ hydrogenation.

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising new medicine. Normally, creating better ...

From CO₂ as 'Waste' to 'Resource'Carbon dioxide (CO₂) is considered the primary culprit behind global warming. If it can be ...

(Nanowerk News) Researchers from Carnegie Mellon University and Los Alamos National Laboratory have used machine learning to create a model that can simulate reactive processes in a diverse set of ...

When chemists design new chemical reactions, one useful piece of information involves the reaction's transition state—the point of no return from which a reaction must proceed. This information allows ...

MIT chemists have developed a computational model that can rapidly predict the structure of the transition state of a reaction (left structure), if it is given the structure of a reactant (middle) and ...