The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.

PNNL data scientists Ján Drgoňa and Draguna Vrabie are working to reduce deployment costs of advanced energy control systems for buildings.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

PNNL and Microsoft Quantum partner to link quantum circuits to powerful government supercomputers.

Pacific Northwest National Laboratory researchers developed a graphical processing unit (GPU)-centered quantum computer simulator that can be 10 times faster than any other quantum computer simulator.

Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.

PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.

Brian Milbrath, a physicist in PNNL’s National Security Directorate, was named a senior member of the Institute of Electrical and Electronics Engineers (IEEE).

In a new video series this fall, PNNL is highlighting six scientific and technical experts in the national security domain. Each was promoted to Scientist and Engineer Level 5, one of PNNL’s most senior research roles.

Infusing data science and artificial intelligence into electron microscopy could advance energy storage, quantum information science, and materials design.

Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.

PNNL researchers devised a new method to probe the atomic structure of plutonium-containing microcrystals using laboratory-based equipment.

PNNL’s expertise is the foundation for monitoring technology that identifies trace amounts of radioactive materials and determines whether they are indicative of a nuclear explosion.

In recognition of Nuclear Science Week on Oct. 19-23, Pacific Northwest National Laboratory reflects on more than half a century of advancing nuclear science for the nation’s energy, environment, and security frontiers.

Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.

PNNL researchers used machine learning to develop a tool for a nonprofit to identify orthopedic implants in X-ray images to improve surgical speed and accuracy.

The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.

PNNL scientists have created a tool called WatchOwl to collect more than 4 million tweets per day related to the COVID-19 pandemic. The tool analyzes tweets related to interventions like social distancing and movement restrictions.

Embedding the known physics of the system to be controlled in the AI model of the system is data efficient and provides safety guarantees.

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.