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 ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

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