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 formulated a new type of dual-ion cell chemistry that uses a zinc anode and a natural graphite cathode in an aqueous—or “water-in-bisalt”—electrolyte.

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

PNNL researchers simulated residential battery use and found in-home energy storage can benefit both the power grid and homeowners.

A research effort under the PNNL-led Battery500 Consortium solved a longtime debate surrounding a structure in lithium-metal battery anodes.

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.

Through two U.S. Department of Energy funding calls awarded in 2020, PNNL is partnering with industry and academia to advance battery materials and processes.

PNNL has published a report that sets the foundation for modeling gaps and technical challenges in optimizing hydropower operations for both energy production and water management.

PNNL computational biologists, structural biologists, and analytical chemists are using their expertise to safely accelerate the design step of the COVID-19 drug discovery process.

PNNL led a multi-institutional effort to design a highly active and more durable catalyst made from cobalt, which sets the foundation for fuel cells to power transportation, stationary and backup power, and more.

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.

PNNL’s longstanding grid and buildings capabilities are driving two projects that test transactive energy concepts on a grand scale and lay the groundwork for a more efficient U.S. energy system.

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.

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 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.

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.

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