Machine learning interatomic potentials (MLIPs) have become an essential tool to enable long-time scale simulations of materials and molecules at unprecedented accuracies. The aim of this collection ...

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 from China University of Petroleum (East China), in collaboration with international partners, have reported a ...

A joint research team from NIMS, Tokyo University of Science, and Kobe University has developed a new artificial intelligence ...

Found in knee replacements and bone plates, aircraft components, and catalytic converters, the exceptionally strong metals known as multiple principal element alloys (MPEA) are about to get even ...

Researchers from China University of Petroleum (East China), in collaboration with international partners, have reported a comprehensive review of ...

Large language models are powering a new generation of AI agents that could transform computational chemistry from a ...

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

When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...

In recent years, power consumption by machine learning technologies, represented by deep learning and generative artificial ...