Svitlana Volkova uses natural language processing and AI to reveal how misinformation and disinformation spread through social media.

PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in California’s San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.

Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.

PNNL is lending analytics expertise to a new first-of-its-kind electric-vehicle carsharing program being launched in Hood River, Oregon.

U.S. Secretary of Energy Jennifer M. Granholm virtually visits PNNL, one of several national lab visits she is conducting.

Svitlana Volkova, chief scientist for decision intelligence and analytics at PNNL, was invited as a panelist at the SIAM International Conference on Data Mining

A new report finds small modular reactors could provide competitively priced electricity in Washington state's future electricity market.

Aaron Luttman, a mathematician and senior technical advisor at PNNL, was invited as a guest speaker during the 2021 National Math Festival.

PNNL researchers are using explainable artificial intelligence to develop new ways to understand and interpret data for national security.

PNNL data scientists Svitlana Volkova and Emily Saldanha, along with former PNNL intern Pamela Bilo Thomas, will publish their research on online information spread in Nature's Scientific Reports.

Explainable artificial intelligence—understanding and explaining the reasoning behind AI decisions—is a necessity for national security.

Sentry-SECURE is a new communication and response platform developed by PNNL, VPI, and Microsoft Azure that rapidly and securely transfers radiological alarm data through the cloud.

PNNL teamed with academia and industry to develop a novel zero-emission methane pyrolysis process that produces both hydrogen and high-value carbon solids suitable for an array of manufacturing applications.

PNNL’s newest solvent captures carbon dioxide from power plants for as little as $47.10 per metric ton, marking a significant milestone in the journey to lower the cost of carbon capture.

Michael Henry, a senior data scientist at PNNL, has accepted a joint appointment at the Texas A&M University RELLIS Center for Applied Research and Experiential Learning.

On the looming 10th anniversary of the Fukushima disaster at the Daiichi Power Station in Japan, PNNL looks back at the science and solidarity it has shared with Fukushima and its nuclear cleanup effort.

PNNL designed a free, web-based tool to visually explore the National Response Framework.

Fifty-eight PNNL staff members were recognized as members of enterprise-wide teams that helped address challenges in national health and security through transformative science and technology solutions.

Explainable AI helps scientists understand and untangle the threads of information that the system uses to make choices or recommendations.

PNNL data scientists Henry Kvinge and Ted Fujimoto presented their research on few-shot learning and reinforcement learning, respectively, at workshops during the 2021 AAAI Conference on Artificial Intelligence.