PNNL researchers are helping to better define the need for grid energy storage in future clean energy scenarios, as well as working to improve technologies for storing renewable energy so it's available when and where it's needed.
Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.
As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.
Combining its strength in biological sciences and data analytics, researchers at the Department of Energy's PNNL are working to enable a quick response to a biological incident — whether intentional, accidental or natural.