To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.
As the world races to discover solutions for reaching net zero carbon emissions, a PNNL analysis quantifies the economic value of the existing nuclear power fleet and its carbon-free energy contributions.
To support federal energy agencies in meeting renewed environmental policies, PNNL is identifying the mechanisms and practices that could enhance agencies’ existing environmental justice programs, policies, and activities.
A Q&A with Lauren Charles, veterinarian and PNNL data scientist, on zoonotic diseases and the role biosurveillance plays in mitigating the growing threat to global health.
Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.
PNNL streamlines environmental review process for advanced reactors, saving years and millions of dollars toward deployments of new nuclear power projects.
PNNL scientists joined international leaders in artificial intelligence research to discuss the latest advances, opportunities, and challenges for neural information processing—the foundation for AI.