Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.

Fish biologist Garrett Staines leads Triton Field Trials research on marine animal behavior and collision risk associated with marine energy devices.

Two PNNL researchers, one a world-leading authority on microorganisms, the other an expert on coastal ecosystem restoration, have been elected fellows of the American Association for the Advancement of Science.

PNNL researchers say that offshore wind energy can add value to the electric grid, beyond just the power it can produce, if locations and strategies are optimized.

Water and energy researchers are invited to join a new task force as a way to collaborate broadly on the intersection of the two topics. The task force is part of IEEE's Power and Energy Society and was launched by PNNL and UU researchers.

PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.

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.

PNNL is one of the collaborating partners on a new grid-scale solar and energy storage installation near the PNNL campus in a project led by Energy Northwest.

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.

PNNL researchers evaluated the accuracy of their software system designed to track bird and bat behavior around remote offshore wind turbines.

Ocean engineer Molly Grear leads Triton Field Trials research studying methods to detect electromagnetic fields associated with marine energy devices.

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.

The Ocean Observing Prize is a competitive incentive program to help inventors advance new concepts for marine energy technologies that can power ocean observing systems, particularly those that inform us about hurricane formation.

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.