The Genesis Mission will mobilize the Department of Energy’s 17 National Laboratories, industry, and academia to build an integrated discovery platform.
Researchers at PNNL share a research- and practitioner-informed approach to assess the threat landscape, elicit and integrate feedback into solutions, and ultimately share outcomes with the emergency response and public safety community.
A breakthrough at PNNL could free friction stir from current constraints—and open the door for increased use of the advanced manufacturing technique on commercial assembly lines.
Two new publications provide emergency response agencies with critical insights into commercially available unmanned ground vehicles used for hazardous materials response.
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.
A team from PNNL contributed several articles to the Domestic Preparedness Journal showcasing recent efforts to explore the emergency management and artificial intelligence research and development landscape.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
At the National Homeland Security Conference, researchers shared how partnerships and emerging technologies like artificial intelligence can play a key role in emergency management preparedness and response.
