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 researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
PNNL and collaborators developed new models—recently approved by the U.S. Western Electricity Coordinating Council (WECC)—to help utilities understand how new grid-forming inverter technology will enhance grid stability.
Understanding the risk of compound energy droughts—times when the sun doesn’t shine and the wind doesn’t blow—will help grid planners understand where energy storage is needed most.
PNNL led one of five Pathway Summer School programs nationwide, with a specific focus on engaging students from Native American or Indigenous backgrounds.
Physicist Emily Mace will share her science journey and an interactive presentation about her current research with middle school and high school students from across the country at the National Science Bowl.
PNNL researchers developed a new model to help power system operators and planners better evaluate how grid-forming, inverter-based resources could affect the system stability.
Rotational Hammer Riveting, developed by PNNL, joins dissimilar materials quickly without preheating rivets. The friction-based riveting enables use of lightweight magnesium rivets and also works on aluminum and speeds manufacturing.
PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in California’s San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.
PNNL licensed two technologies to generate hydrogen. One, a reactor design, generates hydrogen from natural gas. The second innovation uses a 3D printing method to economically manufacture the generator.
