A new physics-embedded machine learning framework called SPEL-VFL reconstructs hidden hydrogen energy flows in smart grids ...

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 ...

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.

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 ...

A new review in the Journal of Materials Science maps how machine learning, from graph neural networks to large language models, is accelerating the design of high-entropy alloy catalysts across vast ...