Researchers at PNNL advised elementary and middle school student teams with their problem-solving research for the FIRST® LEGO® League robotics competitions.
By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.
PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.
A new analysis shows how renewable energy sources like solar, wind and hydropower respond to climate patterns, and how utilities can use this data to save money and invest in energy storage.
A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
Three PNNL-supported projects are at the forefront of developing advanced data analytics technologies to enhance the U.S. power grid’s reliability, resilience, and affordability.
The National Transmission Planning Study presents several transmission expansion scenarios that would reliably support the growing demand for energy across the nation.
The Grid Storage Launchpad dedication event was attended by leaders in grid and transportation energy storage, battery innovation, and industry stakeholders working to transform America’s energy system.
