PNNL mathematician and AI researcher Henry Kvinge bridges math and AI, finding connections between the two fields and studying ways where they can foster mutual progress.

PNNL’s nondestructive evaluation capabilities support advancements in nuclear energy, including research for the U.S. Nuclear Regulatory Commission to preserve the nation’s existing nuclear fleet.

PNNL convenes leaders from the Department of Energy, national laboratories, computing industry and academia for a two-day workshop to advance quantum computing for computational chemistry.

Scientists are optimizing microbes to harvest critical minerals and produce bioproducts using AI and autonomous lab equipment.

Custom AI research assistant allows users to ask questions and get answers from hundreds of wildfire mitigation plans.

Automated liquid handling, combined with data analysis and AI, optimizes microbiological growth conditions at PNNL.

Autonomous science laboratories are taking shape quickly across the PNNL campus.

An award-winning computing method called poly-streaming accelerates the analysis of massive datasets while using limited memory.

Predicting how organisms’ characteristics respond to not only their genes, but also their environments (a nascent field called predictive phenomics), is extraordinarily challenging. Researchers at PNNL are using AI to tackle that challenge.

Quantum computing promises leaps in chemistry and materials science, and PNNL is preparing to realize its potential with a collaborative approach.

PNNL chemist and AI scientist Nancy Washton invited to present on AI literacy at National Science Bowl.

Formal mathematics both reveals what’s inside the black box of AI algorithms and pushes the boundary of what’s possible within math as a discipline.

Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.

Nine national laboratories, including PNNL, bring together over 1,000 scientists for a day to use AI to accelerate scientific discovery.

Scientists are using artificial intelligence and powerful computing to sculpt new molecules in an effort to treat disease.

The search for dark matter includes expertise in radio frequency signal detection, quantum sensing, and high-energy physics at PNNL.

Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

Artificial intelligence, high-throughput experimentation, and materials science expertise combine to efficiently develop next-generation energy storage materials.

Researchers are planning for an electric grid that deploys machine learning to think ahead, plan for the worst, anticipate demand, and meet consumer needs safely and securely.

James Koch, a data scientist, developed a technique that enables high-fidelity remote sensing with limited data.