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.
Scientists have created a single-crystal, nickel-rich cathode that is hardier and more efficient than before—important progress on the road to better lithium-ion batteries for electric vehicles.
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.
Clarivate Analytics recently unveiled its 2020 list of Highly Cited Researchers. The list named 17 PNNL scientists for their influential and oft-referenced work.
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.
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.
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.
The MIT-sponsored competition encourages community approaches to developing new solutions for analyzing graphs and sparse data; PNNL has placed a winner in each year.
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.
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.
Sharon Hammes-Schiffer, deputy director of the Center for Molecular Electrocatalysis (CME), has received awards from both the Royal Society of Chemistry and the American Chemical Society.
Making sure there’s enough electricity at the lowest price is a critical endeavor undertaken daily by electricity market operators. Now, there’s an approach that provides more timely and accurate information to make day-ahead decisions.