A research buoy managed by PNNL has been deployed in Hawai’ian waters, collecting oceanographic and meteorological measurements off the coast of O’ahu.

The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.

PNNL is making waves in pursuit of a blue economy. Researchers are advancing science and technology to expand—and protect—the gifts of the sea.

New PNNL-developed nanogenerator harnesses the renewable energy in ocean waves to power sensors that provide critical weather and wave information.

PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.

STEM Education programs at DOE and national labs offer environmental management internships; applications are due soon for summer 2023.

New PNNL research makes it easier to differentiate between chemical and nuclear explosions.

A review article led by researcher Jade Holliman explores the different classes of metamaterials, from the underlying fundamental science to potential applications.

Researchers developed a machine learning model that can analyze chemical reactions as they happen in an electron microscope.

Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.

As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.

Multidisciplinary teams from research and industry are brought together using management systems developed by a team of software engineers at PNNL.

PNNL researchers developed the dummy payload to evaluate the performance of marine energy device prototypes in the Powering the Blue Economy: Ocean Observing Prize Competition.

A review article examines a decade of work on the atom-scale process of turning carbon dioxide into stable minerals.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.

Some rocks can potentially convert injected carbon dioxide into more stable solid minerals. A new review article explores what scientists know about the atom-by-atom process.

Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.

Biochemical preservation and mineral association retain carbon in grassland soils, resulting in consistent molecular composition across ecosystems.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.