Nuclear reactors need tough alloys that can withstand extreme conditions. PNNL researchers developed a computational approach called robust alloy design (RAD) to search for materials that meet multiple nuclear requirements.

The Microbial Molecular Phenotyping Capability has been designed to transform how we could put microbes to work for American manufacturing competitiveness and human health advances, among other benefits.

Scientists combined detailed images and coordinated time-series multiomics data to show how protein complexes regulate carbon fixation as light conditions change.

A PNNL team is working to counter the negative impacts of fentanyl in the environment. Their journal article was selected this summer by the Journal of Environmental Quality as its outstanding paper of 2025.

Existing stream monitoring efforts capture some fire-affected regions, but most fires are in places without ongoing water quality monitoring.

A new modeling approach uses burn severity maps to test how reduced infiltration shifts surface water from soil penetration into streams after wildfire.

Model simulations in humid and semi-arid basins revealed distinct thresholds where wildfires begin to significantly alter river water flows and dissolved nutrient transport.

Researchers developed a new technique that combined mass spectrometry and label-free optical imaging to map molecular and structural changes in healthy and diseased lung tissue, providing new insight into bronchopulmonary dysplasia.

PNNL partners with SRNL, FIU, and industry to test fixative technologies that could be used to immobilize radioactive contaminants on the surface of building materials during the deactivation and decommissioning of DOE legacy facilities.

Across 47 sites in the Yakima River Basin of Washington State, faster oxygen consumption occurred with warmer water, more nutrients, and more suspended solids.

Researchers reveal how uncharacterized molecules affect the diversity and composition of dissolved organic matter in rivers.

Measurements show river flow volumes and seasonal timing have shifted; models project where flows will rise, fall, or shift in the future.

Artificial intelligence helps analyze images and reduce uncertainty for a key measure of watershed function.

Dynamic organic matter traits tied to reactions can surpass static descriptors in explaining decomposition rates and responses to environmental change.

Using an AI approach to combine outputs from microbial models and apply them as inputs to reactive-transport models reduces computational time by several orders of magnitude.

Made with less than 0.15 percent polymer, the material quickly seals damage and restores strength across repeated cracking cycles.

Using multiple specialized techniques, IDREAM researchers gained a better understanding of how trace impurities within gibbsite affect the hydrogen yield.

Integrating experiments and modeling show how a fungal exudate-inspired substrate mixture elicits an emergent growth phenotype and metabolic responses in Pseudomonas putida.

By selectively stabilizing either a right- or left-handed helical pose of its substrate, an enzyme tunes the final product.

A decade-long evolution in making omics data easier to analyze earns widespread recognition.