As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...

The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...

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 ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...