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.

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

Short-term flooding of an experimental coastal forest impacted soils but not trees, with implications for understanding ecosystem disturbance responses.

Lab experiments show that just a few saltwater pulses can rapidly alter soil pore structure and reduce oxygen flow, stressing tree roots in coastal forest soils.

Differences in dissolved organic matter between rivers and estuaries follow similar patterns across freshwater and saltwater coasts.

Newly designed sensor network comprehensively monitors a range of coastal landscapes to better understand nutrient and elemental dynamics that drive ecosystem function.

Exploring how shifting boundaries between upland and wetland areas influence soil processes and signal early ecosystem transformations.

A high-performance, scalable pipeline transforms raw high frequency coastal sensor data into research-ready datasets.

Global exercise advances nuclear forensic science and investigative capabilities.

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

Five PNNL innovations earned 2026 R&D 100 Awards for advances in biotechnology, manufacturing, critical minerals, and nuclear security.

An innovative new approach enables direct measurements of electronic effects at solid–liquid interfaces.

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

A new report highlights a public workshop hosted by the National Academies Forum on Microbial Threats and features PNNL's Lauren Charles and the AI-Driven One Health Security program.

Researchers at PNNL have developed an interpretable, lightweight AI model that can easily predict weld microstructure features using only basic machine sensor inputs.

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

Integrating new functions into a genome-scale model enabled researchers to simulate and experimentally validate viral hijacking pathways.

Replacing commercial acid with acidic waste enables researchers to improve nickel extraction efficiency, lower projected costs, and improve process economics.

Researchers discovered that a polymer additive promotes smooth, layer-by-layer deposition on metal electrodes by tuning interactions with the substrate.