Scientists have created a cybersecurity technology that stops hackers from doing damage by feeding them illusory tidbits of success.

The DOE Early Career Research Program supports exceptional researchers during the crucial early years of their careers and helps advance scientific discovery in fundamental sciences

National Nuclear Security Administration Graduate Fellow Marc Wonders has spent the past year working with researchers exploring artificial intelligence in the national security mission space.

A webapp developed by PNNL in collaboration with the University of Washington to help drive efficiencies for urban delivery drivers is now in the prototype stage and ready for testing.

PNNL computer scientists joined international leaders in machine learning to present research to detect and address potential cybersecurity threats and devise epidemic interventions.

With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.

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

Study says planners need to account for climate impacts on renewable energy during capacity development planning to fully understand investment implications to the power sector.

For the second straight year, PNNL researchers are featured in a special edition of the Journal of Information Warfare. This issue explores the topic of macro cyber resiliency.

One year ago, Verizon announced a partnership that made PNNL the U.S. Department of Energy’s first national laboratory with Verizon 5G ultra-wideband wireless technology.

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

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.

Using the connected moments mathematical technique decreases the time and computational power needed for performing quantum computing simulations.

New 140,000-square-foot facility will advance fundamental chemistry and materials science for higher-performing, cost-effective catalysts and batteries, and other energy efficiency technologies.

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.

New approach allows nonexperts to optimize control of a building's energy systems without adding computing power or proprietary software.

Ultra-trace radiation detection technique sets new global standard for measuring the nearly immeasurable.

The partnership to apply artificial intelligence to improve complex systems is part of a U.S. Department of Energy Office of Science $4.2 million, three-year grant.

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.