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

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 ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

Discover how a new machine learning method can help scientists predict which MOF structures are good candidates for advanced ...

A new machine learning tool developed at Princeton will enable researchers to sift through trillions of design options to predict which metal organic framework will be useful in laboratories or ...

The exploration of Haeckelites gained momentum following the experimental synthesis of beryllium oxide (BeO) in this configuration. This achievement sparked interest in the potential of other elements ...

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 ...

If nonliving materials can produce rich, organized mixtures of organic molecules, then the traditional signs we use to recognize biology may no longer be enough.

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...