Study shows the advantages of top-town proteomics for characterizing histones.

PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.

A microbial community expresses a phenotype of interest ~20 percent higher than the sum of each member species.

RemPlex 2025 Global Summit on Environmental Remediation attendees share knowledge about cleanup and monitoring of complex sites worldwide; more than 100 presentations are posted online.

Structural proteomics reveal how cyanobacteria adapt to changing light.

Secretary Wright visited PNNL's campus in Richland, Washington, late last year to meet with innovators in chemistry, biology, computing, and more.

Researchers use multiomics to confirm role of lipid synthesis during infection, leading to model of how to restrict virus replication.

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

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.

Capturing protein structural changes in host cells exposes vulnerabilities exploited by viruses to hijack cellular machinery.

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.

PNNL researchers developed a new computational workflow to study day-to-night gene expression dynamics of cyanobacterium in real time.

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.

Understanding molecular modifications of proteins in the red yeast could help scientists re-engineer the organism’s phenotype.

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

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.

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.