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 ...

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

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

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 ...

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 ...

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

In a groundbreaking development, researchers have unveiled a revolutionary AI-driven periodic table that’s set to transform the landscape of modern ...

Computational Chemistry is the study of complex chemical problems using a combination of computer simulations, chemistry theory and information science. Also called cheminformatics, this field enables ...

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

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...