Filtered by Building-Grid Integration, Chemical Physics, Cybersecurity, Data Analytics & Machine Learning, Materials in Extreme Environments, and Science of Interfaces
Seventeen teams from regional colleges and universities gathered at PNNL Nov. 16 to put their cyber skills to the test by protecting critical energy infrastructure against simulated cyberattacks as part of DOE's CyberForce Competition.
Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.
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.
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.
A gathering of international experts in Portland, Oregon, explored the future of electron microscopy and surfaced potential solutions in areas including new instrument designs, high-speed detectors, and data analytics capabilities.
A PNNL technology enables automated Economic Dispatch, which coordinates the use of energy in a manner that enhances distributed generation, efficiency, renewables, and grid reliability.
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.
A multi-institute team develops an imaging method that reveals how uranium dioxide (UO2) reacts with air. This could improve nuclear fuel development and opens a new domain for imaging the group of radioactive elements known as actinides.
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.
Scientists have taken a common component of digital devices and endowed it with a previously unobserved capability, opening the door to a new generation of silicon-based electronic devices.
Researchers apply numerical simulations to understand more about a sturdy material and how its basic structure responds to and resists radiation. The outcomes could help guide development of the resilient materials of the future.
A radioactive chemical called pertechnetate is a bad actor when it’s in nuclear waste tanks. But researchers at PNNL and the University of South Florida have a new lead on how to selectively separate it from the nuclear waste for treatment.
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.
It’s hot in there! PNNL researchers take a close, but nonradioactive, look at metal particle formation in a nuclear fuel surrogate material. What they found will help fill knowledge gaps and could lead to better nuclear fuel designs.