Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.
PNNL’s Jie Xiao was recently recognized for her outstanding contribution to basic and applied research on lithium-ion batteries and beyond by the International Automotive Lithium Battery Association.
In today’s digital age, the rabbit hole of connected information can be not only a time sink, but downright overwhelming. Even for high-performance computers.
Scientists have uncovered a root cause of the growth of needle-like structures—known as dendrites and whiskers—that plague lithium batteries, sometimes causing a short circuit, failure, or even a fire.
With support from DOE’s Office of Electricity and National Grid, PNNL led a groundbreaking study to accurately assess the full value of grid energy storage investments across a wide variety of use cases.
Twenty-four analysts from U.S. intelligence organizations met in August for a machine learning activity with PNNL researchers Nicole Nichols, Jeremiah Rounds, Lawrence Phillips, and Brian Kritzstein.
PNNL researchers have created a chemical cocktail that could help electric cars power their way through extreme temperatures where current lithium-ion batteries don’t operate as efficiently as needed.
Energy storage is slowly shifting utility planning practices from the current paradigm, which ensures grid reliability by building reserve generation resources, to ensuring grid reliability by optimizing grid services.
Trouble on the electric grid might start with something relatively small: a downed power line, or a lightning strike at a substation. What happens next?
Pacific Northwest National Laboratory is leading efforts to address next-generation computing’s critical role in protecting the nation from cybersecurity threats.
Researchers at the Department of Energy’s Pacific Northwest National Laboratory and Sandia National Laboratories have joined forces to reduce costs and improve the reliability of hydrogen fueling stations.
PNNL researchers demonstrate how the excitation of oxygen atoms that contributes to better performance of a lithium-ion battery also triggers a process that leads to damage, explaining a phenomenon that has been a mystery to scientists.
A new PNNL tool makes it easy to see the differences across the country when it comes to the cost and affordability of electricity. Users can sort and compare nearly 100 metrics or variables and get individual county information.
Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.
PNNL researchers are developing and evaluating bat tagging and tracking tools that will help design solutions to protect the bat population from wind turbines.
