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

Perovskite solar cells have gained considerable momentum in the search for cheaper, more efficient solar energy. However, the ...

AI machine learning uses so much computing power and energy that it's typically done in the cloud. But a new microtransistor, 100X more efficient than the current tech, promises to bring new levels of ...

The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

Researchers have developed a framework that uses machine learning to accelerate the search for new proton-conducting materials, that could potentially improve the efficiency of hydrogen fuel cells.

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

Explore how machine learning enhances energy monitoring in smart homes with CEO Mike Phillips from Sense. This interview covers the application of AI in tracking energy use, detecting potential device ...

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