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

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.

In honor of National Intern Day, PNNL and intern Jonathan Mills were named among the Top 100 in the nation by early-career recruiting firm WayUp.

Diefenderfer, Earth scientist who focuses on coastal ecosystems at PNNL, recently published “Ten Years of Gulf Coast Ecosystem Restoration Projects Since the Deepwater Horizon Oil Spill,” a cover article.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

As wildfires grow increasingly severe, PNNL researchers are working to slow their spread and mitigate their harmful effects.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

ICON science is a Department of Energy-developed framework to enhance scientific outcomes via more intentional design of research efforts across all domains of science.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

An analysis of land use in watersheds that supply drinking water to over a hundred United States cities identified a wide range of exposure to potential contamination.

PNNL dual appointee Nathan Kutz is one of 26 mathematicians and computer scientists to be selected this year.

PNNL scientists are taking part in a Department of Energy climate science field campaign in the Rocky Mountains of Colorado.

New facility will accelerate energy storage innovation, increase clean energy adoption and grid resilience.

PNNL experts perform fundamental climate science work at multiple scales to understand impacts on energy, water, food, and infrastructure systems.

Morris Bullock received an award and PNNL staff organized symposia and presented exciting research.

Surface characterization allows researchers to explore the compatibility between different solvent-membrane combinations.

PNNL Chief Scientist for Computing Jim Ang will be part of a DOE Office of Science virtual discussion regarding industry collaborations on AI hardware.

PNNL data scientist to edit collection of research articles focused on understanding how microcircuits function in the brain and in artificial intelligence systems.

A paper co-authored by Courtney Corley was recently selected as the most influential paper for the Twenty-First National Conference on Artificial Intelligence.