Exploring why some brains are more resilient to the impact of Alzheimer’s disease could lead to improved diagnoses, treatment and prevention.

A team from the Environmental Molecular Sciences Laboratory published research, demonstrating that the soil microbes were directly involved in the stabilization of soil organic carbon and mineral weathering.

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

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

Samantha Erwin was one of six speakers during the Careers Using Mathematics panel at the Nebraska Conference for Undergraduate Women in Mathematics.

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 scientists carve a path to profit from carbon capture by creating a system that efficiently captures CO2 and converts it into one of the world’s most widely used chemicals: methanol.

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

A collaborative effort led by PNNL researchers analyzed decarbonization pathways for Argentina, Chile, Egypt, Indonesia, and Nigeria.

The Joint Appointment program at PNNL is one of the most diverse among other U.S. national laboratories, involving nearly 60 universities and research institutions in the United States and abroad.

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

For a second year in a row, doctoral intern Jack Watson was awarded the Student Merit Award by the Society for Risk Analysis and the Resilience Analysis Specialty group.

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.

A PNNL team developed and used a model framework to understand the performance and structural reliability of a state-of-the-art solid oxide electrolysis cell design.

Iron-based fertilizer may stimulate plankton to pull carbon dioxide from the ocean, driving a carbon-negative process.

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.

A new project will produce a database of optimized conditions for efficient, carbon negative recovery of energy-relevant minerals in red mud waste.