Artificial intelligence/Machine Learning-driven modeling reduces time-to-market for faster Design Technology Co-Optimization ...

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

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 ...

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

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 ...

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

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

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 ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...