Tailored peptoid-based assemblies mimic metal-free enzymes with significantly higher stability.

Researchers at PNNL are sharing work grounded in One Health, which connects human, animal, plant, and environmental data to improve situational awareness, early warning, and decision-making.

Researchers discovered that frustrated electric forces drive a novel precipitation pathway called microphase separation and identified a precursor intermediate state of ordered ion networks.

Assistant Secretary Katie Jereza toured PNNL capabilities that translate laboratory innovation into operational and industry impact.

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.

Scientists uncovered the molecular basis of nitric acid speciation across dilute and concentrated solutions and identified competing hydration-shell rearrangements around lanthanide ions at the dilute limit.

A new memorandum of understanding creates a framework for expanded research, talent development, and technology transfer between Georgia Tech and PNNL.

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.

Yong Wang’s joint appointment connects PNNL, WSU, and the next generation of scientists.

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.

Researchers showed that spiking neural networks can be accurate for regression problems, opening opportunities for efficient neuromorphic computing.

PNNL scientists were among the specialists keeping the crowds safe at the recent FIFA World Cup competition.