The Journal of Chemical Physics

A research team has developed a unified theoretical framework to better predict the performance of single-atom catalysts for electrochemical carbon dioxide reduction.

Researchers from SANKEN (The Institute of Scientific and Industrial Research) at Osaka University and two other universities used topological data analysis to improve the predictions of physical properties of amorphous materials by machine-learning algorithms. This may allow for cheaper and faster calculations of material properties.