EZBattery Model allows energy storage researchers to more quickly and easily identify the best performing battery designs without the need for extensive physical prototyping or computationally expensive simulations.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

PNNL is supporting the floating offshore wind industry to enable gigawatt-scale development of floating offshore wind in the United States while minimizing environmental impacts and supporting local workforces.