Scientists have taken a key step toward harnessing a form of AI known as deep reinforcement learning to protect computer networks.

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.

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

Research published in Journal of Manufacturing Processes demonstrates innovative single-step method to manufacture oxide dispersion strengthened copper materials from powder.

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 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.

The American Chemical Society Richland Section has been recognized by its national organization with the Best Overall Section Minority Affairs award for 2022.

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.

A paper from PNNL and Southern California Edison describing new methodologies for assessing electric vehicle impacts to the grid was selected as a best paper by IEEE.

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

A new extrusion process eliminates pre-heating to provide significant energy savings during production of extruded aluminum alloys.

A new longer-lasting sodium-ion battery design is much more durable and reliable in lab tests. After 300 charging cycles, it retained 90 percent of its charging capacity.

Energy storage expert Ji-Guang (Jason) Zhang was honored by DOE with a Distinguished Achievement Award.

The first-ever simulation of aluminum conductivity offers a recipe for an inexpensive, lightweight alternative to copper.