Machine learning reveals 5-angstrom sweet spot behind metallic glass stability

Using the second-nearest neighboring atoms to predict metallic glass stability can help researchers more accurately model the disordered solid with strong, elastic properties, according to a recent ...

Machine learning proves that graphene is hydrophobic

For more than a decade, a fundamental mystery has surrounded graphene—the one-atom-thick "wonder material" known for its ...
Michigan Technological University

Researchers Apply Machine Learning and AI in Search of Less Costly Electronic Structure Method

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 ...

AI shapes the design of the electron-ion collider

Artificial intelligence and machine learning are shaping major design and research decisions for the planned Electron-Ion ...
Labroots

Crystal Structures and Machine Learning, Potential New Age of Renewable Energy Storage

A recent study published in Nature Materials examined how machine learning is used to reveal the atomic mechanisms of argyrodites, which could open the doors for a new age of energy storage. This is ...
Nanowerk

Machine learning uncovers new semiconductors with unique square-octagonal structure

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 ...