A modeling study shows that adding batteries to a dam could decrease the wear and tear on hydropower turbines and open up new opportunities for dam operators to earn revenue.

Delivering excellence in power systems and electric grid advancement earns two PNNLers the association’s top distinction.

Mystery of how important aluminum minerals form and dissolve solved with materials science and advanced imaging studies.

Nanosize platelets of an aluminum material slide and join in a staggered orientation to form larger crystals.

Early career researchers recognized with Team Science Award by the Department of Energy for presentation highlighting the collaborative science performed by IDREAM.

PNNL researchers Daniel Deng and Yehia Ibrahim join the 2025 class of National Academy of Inventors Fellows.

IDREAM researchers uncovered how dimeric complexes control how aluminum hydroxide minerals dissolve.

Emma Cotter appointed to leadership team of consortium of universities focused on advancing marine energy.

From developing new energy storage materials to revealing patterns of Earth’s complex systems, studies led by PNNL researchers are recognized for their innovation and influence.

ThermalTracker-3D can help streamline permitting, reduce costs, and shorten development time of energy projects.

PNNL’s SHAD-TAGS+ allows researchers to monitor fish species to help inform energy project development.

The ability of a storm-resolving weather model to predict the growth of storms over central Argentina was evaluated with data from the Clouds, Aerosols, and Complex Terrain Interactions (CACTI) field campaign in central Argentina.

Researchers have developed the first coastal transport model for microplastics to understand how particles move in waterways and coastal currents.

The Department of Energy Art of Science contest entry focuses on the extraordinary universe of chemical bond making and breaking under irradiation.

Trace amounts of iron and chromium can incorporate into gibbsite, affecting how the mineral dissolves.

Researchers from PNNL and Parallel Works, Inc., applied machine learning methods to predict how much oxygen and nutrients are used by microorganisms in river sediments.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

Experiments focus on catalysts for off-road vehicles that optimize the use of critical minerals while lasting longer and costing less.

Lakes are important sentinels of climate change and contribute significantly to the emissions of the second most important greenhouse gas—methane.

The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.