Researchers build visibility for PNNL through involvement in national workshop reports while helping shape DOE’s future research priorities.

Genesis Mission awards to PNNL will advance scientific discovery, next-generation energy systems and advanced manufacturing, among others.

Award-winning research advances AI applications for environmental cleanup.

PNNL researchers demonstrate high-purity production of two essential gases to ensure a U.S. domestic feedstock for advanced quantum computing.

PNNL has named atmospheric scientist Larry Berg director of the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) User Facility, where he will oversee a global network of atmospheric research observations.

A team at PNNL support the Joint Actinide Shock Physics Experimental Research program.

New software enables the study of nuclear quantum effects in large, condensed phase systems up to 10× faster than traditional methods.

Protein and water environments set the overall redox scale of iron-sulfur clusters, but local coordination geometry fine-tunes the final potential.

New theoretical framings of quantum dynamics enable better quantum-based simulation of molecular systems and dynamics.

Developed a method for selectively anchoring diverse divalent metal cations in zeolites, important for precise control over catalytic materials.

Developed a simple kinetic framework for evaluating catalyst hydride transfer ability.

PNNL has formed a partnership with the Orlando-based firm Refinity, which has licensed a key process from PNNL that will help the company convert mixed plastic waste into valuable industrial products like chemicals, plastics, and fuels.

The Department of Energy’s Transportation Technologies Office has issued two 2026 Annual Merit Review Awards to researchers from PNNL. Both awards recognize PNNL researchers whose work is reducing the need for critical materials.

Chiral nanotubes facilitate the direction-specific diffusion of carbon dioxide to be faster than nitrogen gas.

A newly published custom collection of glass formulas for nuclear waste vitrification — developed and validated by PNNL over the past three years — was made possible in that timeframe with AI tools, including a PNNL machine learning model.

At the summit, PNNL engaged with partners and investors, highlighting seven projects that accelerate the deployment of new energy technologies.

An international research team deployed AI-powered computing to solve important chemical structures for energy applications using NVIDIA hardware.

PNNL chemist Sarah Saslow received the ACS Rising Star Award for her research supporting environmental cleanup, including work on legacy waste and subsurface contamination.

The underlying crystal structure of carbonate surfaces plays a key role in the formation of cobalt mineral structures on these surfaces.

A suite of new modeling methods gives researchers better tools to predict molecular behavior inside cavities.