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

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

PNNL’s contributions over the last year span scientific discovery, sustainable energy and national security.

Manish Sharma, a physicist at PNNL, has been nominated to serve on the Radiation Protection and Shielding Division Executive Committee.

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.

Advancing the science of radiation, especially among students at minority-serving institutions, is the goal of one of the Department of Energy’s newest consortia.

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

Twenty years after the first radiation portal monitor was installed, PNNL continues supporting the Department of Homeland Security’s efforts to detect and prevent terrorist weapons from crossing our borders.

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.

PNNL experts in nuclear forensics helped lead laboratories around the world through a rigorous test involving nuclear materials.

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.