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.
Two PNNL interns are behind recent innovation in real-time testing and continuous monitoring for pH and the concentration of chemicals of interest in chemical solutions; outcomes have applicability not only to nuclear, but to industries.
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.
Risk analysis on the plutonium-fueled power system that supplies electricity to the Mars rover answered the “what if” nuclear safety questions for NASA.