Developing a new understanding of the structure of natrophosphate, a complex mineral found in radioactive tank waste at the Hanford Site, by integrating experimental techniques.

New research makes molecular-level calculations of water faster and easier.

James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference.

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

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

Eight PNNL research papers were recognized by the 2022 Waste Management Symposia as “Papers of Note” and “Superior.” One paper received a Best Oral Paper/Presentation Award.

The size and concentration of ions influences the aggregation behavior of solutions of boehmite.

Business, industry, and government careers were a focus of the PNNL-led Mathematics Research Communities conference.

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.

PNNL’s Rob Howard received the 2022 Fuel Cycle and Waste Management Award from the American Nuclear Society.

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

Researchers are studying the chemical reactions that occur when oxygen mixes into the surface of oxide materials.

The size of the alkali metal within the material influences the crystallization pathway.

PNNL scientists developed new capabilities to study materials under extreme conditions.

Two PNNL teams have been recognized for their work on safe, secure radioactive material shipping.

PNNL Materials Scientist Leo Fifield recognized for contributions to the field of nuclear instrumentation and control.

PNNL nuclear engineer Casey Spitz has qualified as a Criticality Safety Engineer-Analyst, making him one of nine staff members who are responsible for the safe condition of fissionable materials.

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

To support federal energy agencies in meeting renewed environmental policies, PNNL is identifying the mechanisms and practices that could enhance agencies’ existing environmental justice programs, policies, and activities.

Performing a network analysis of forces between particles reveals new insight into shear induced thinning and thickening in non-Newtonian fluids.