Newly uncovered structure-composition relationship could help to improve AI's ability to predict new inorganic materials ...

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

A research team from the University of Xiamen has developed a machine learning potential specifically for Pt-water interfaces. This research harnessed machine learning molecular dynamics to uncover ...

There are few problems now that AI and machine learning cannot help overcome. Researchers from the Yokohama National University are using this modern advantage to resolve what conventional methods ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

Researchers have used machine learning to create a model that simulates reactive processes in organic materials and conditions. Researchers from Carnegie Mellon University and Los Alamos National ...

Chemists have created a machine learning tool that can identify the chemical composition of dried salt solutions from an image with 99% accuracy. By using robotics to prepare thousands of samples and ...

A research team at the University of Xiamen has created a machine learning potential for Pt-water interfaces. This study used molecular dynamics machine learning to uncover the complex interactions at ...