In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.
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 is honoring its postdoctoral researchers as part of the fourteenth annual National Postdoc Appreciation Week with seven profiles of postdocs from around the Laboratory.
Four PNNL researchers received highly competitive DOE Early Career Research Program awards, providing five continuous years of funding for their projects.
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.
A webapp developed by PNNL in collaboration with the University of Washington to help drive efficiencies for urban delivery drivers is now in the prototype stage and ready for testing.
Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.
Twelve energy-related technologies developed at PNNL have been selected for additional technology maturation funding to help move them from the laboratory and field tests to the marketplace.
After years of planning, building, and calibration, researchers at the Belle II accelerator experiment in Japan have published their first physics paper.
Researchers at PNNL are contributing artificial intelligence, machine learning, and app development expertise to a U of W project that will ease challenges with urban freight delivery. The project will provide delivery drivers with a tool