Some of the most encouraging results for reaction-enhancing catalysts come from one material in particular: tin (Sn). While ...

Semiconductor processing is notoriously challenging. It is one of the most intricate feats of modern engineering due to the ...

A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

Floods are some of the most devastating natural disasters communities in the United States face, causing billions of dollars ...

The new capabilities are designed to enable enterprises in regulated industries to securely build and refine machine learning ...

Researchers from The University of Texas at Austin used machine learning and artificial intelligence to develop new materials that could keep your house cooler and reduce energy bills.

In a first, Australian scientists turned to quantum machine learning to model semiconductor design, outperforming classical ...

Researchers at Tohoku University used machine learning potential to create large-scale models of tin (Sn) catalysts under ...

To transition from LLMs to AGI, we need to overcome several major limitations and introduce fundamentally new capabilities ...

Innovative AI techniques in cement formulation lead to eco-friendly mixes, significantly cutting emissions and improving ...

A new study finds rare neural stem cells in the adult human hippocampus, suggesting some brains can generate new neurons into ...

New research reveals a surprising geometric link between human and machine learning. A mathematical property called convexity ...