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.
PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence
PNNL advisors joined a panel of Washington State emergency management personnel to discuss how partnerships with national laboratories are enabling science and technology solutions.