Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

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

Electro- and photocatalytic materials are central to enabling sustainable energy conversion processes such as water splitting, CO2 reduction, oxygen ...

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

A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...

The human brain, with its billions of interconnected neurons giving rise to consciousness, is generally considered the most powerful and flexible computer in the known universe. Yet for decades ...

Jeremy Goecks (left) is the Assistant Center Director for Research Informatics at the Moffitt Cancer Center (FL, USA), where he is also an Associate Faculty Member in the Department of Machine ...

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

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...