Embedding the known physics of the system to be controlled in the AI model of the system is data efficient and provides safety guarantees.

A 2011 earthquake and tsunami in Japan that knocked out a nuclear power plant helped inspire PNNL computational scientists looking for clues of future nuclear reactor mishaps by tracking radioactive iodine.

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing

Artificial intelligence helps researchers identify metabolites, the small molecules that underlie life.

PNNL researchers and professional staff led discussions ranging from biothreats and climate change to science careers at the 2020 annual meeting of the American Association for the Advancement of Science, held this year in Seattle.

First-of-its-kind network analysis on a supercomputer can speed real-time applications for cybersecurity, transportation, and infectious disease tracking

In a special edition of the Journal of Information Warfare, Pacific Northwest National Laboratory researchers explore the revolution of technologies defending the nation’s critical infrastructure.

Researchers have identified two processes responsible for fracturing rock at lower pressures for geothermal energy production using PNNL’s fracturing fluid, StimuFrac™.

At a conference featuring the most advanced computing hardware and software, ML in its various guises was on full display and highlighted by Nathan Baker’s featured invited presentation.

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.

Global climate change is often at the forefront of national and international discussions and controversies, yet many details of the specific contributing factors are poorly understood.

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.

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.

PNNL researchers are developing the only tool that can control large-scale distributed energy resources in real time.

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.

A study co-led by PNNL and reviewed in Science investigates how nanomaterials—both ancient and modern—cycle through the Earth’s air, water, and land, and calls for a better understanding of how they affect the environment and human health.

Researchers at PNNL are developing a new class of acoustically active nanomaterials designed to improve the high-resolution tracking of exploratory fluids injected into the subsurface. These could improve subsurface geophysical monitoring.