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.

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

Fish biologist Brenda Pracheil has been named chair of the Low Impact Hydropower Institute focused on reduction of impacts of hydropower dams on the environment.

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.

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.

Despite severe drought, a new report shows that hydropower remains a strong and steadfast contributor of renewable energy in the West.

Biomedical scientist George Bonheyo has been selected as chair of a new International Electrotechnical Commission committee charged with creating standards for researching and measuring biofouling on marine energy systems.

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.

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

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

Recognizing how innovation and clean technologies at the very edge of the grid can work together to transition the electricity system, PNNL takes a multidisciplinary approach to advancing and integrating renewable energy solutions.

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