A research team led by UCLA and the University of Rochester has demonstrated a promising evolution of an imaging system ...

Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional materials that may host unusual quantum behavior. The work, published in ...

Discover how a new machine learning system designed for physical signals could provide a boost for medical imaging and autonomous vehicle sensors.

Machine learning is rapidly reshaping how we model molecules, and a growing body of work suggests that neural networks are not merely statistical ...

Abstract: Machine learning stands poised to revolutionize the process of scientific discovery across various disciplines. In this talk, we will introduce a state-of-the-art scientific machine learning ...

Physics-informed machine learning connects atomic structure with ion transport and electrolyte stability, accelerating better sodium- and lithium-ion batteries.

Finding a reasonable hypothesis can pose a challenge when there are thousands of possibilities. This is why Dr. Joseph Sang-II Kwon is trying to make hypotheses in a generalizable and systematic ...

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...

Image courtesy by QUE.com For decades, the search for room-temperature superconductors has been one of physics' most ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...