In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

PNNL researchers studied the microstructure of lithium silicates under emulated fusion conditions.

Combining cold spray deposition and friction stir processing for a more efficient route to oxide dispersion strengthened steel.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.

To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.

Researchers studied the boundary precipitation of tungsten heavy alloys in an extended high temperature irradiation environment

A new approach validates quantum algorithms for low-energy nuclear physics applications

PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.

The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.

The software democratizes hardware designs by enabling domain scientists to design their own accelerators.

PNNL recently partnered with Amazon Web Services for AWS GameDay, a gamified learning event that challenges participants to use AWS solutions to solve real-world technical problems in a team-based setting.

Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.

Researchers designed ultra-low radiation cables to reduce background noise for highly sensitive neutrino and dark matter detectors.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

PNNL’s DataLife tool analyzes and identifies bottlenecks in scientific workflows.

Ripples demonstration will take place at the DOE booth at the International Conference for High Performance Computing, Networking, Storage, and Analysis.

PNNL signs memorandum of understanding with Oregon State University to support marine science and technology advancements.

A new tool helps identify non-powered dams across the country that are top candidates for conversion to power-generating hydroelectric facilities.

The report explores how research in planning, data, policy, and technology can address some of the underlying challenges facing water power systems.