Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.
Now, anyone can easily explore and access data from a nationwide map of data centers, the infrastructure that powers them, and projections of future data center locations.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.