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.

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.

Anisotropies in surface potential driven by competitive ion adsorption can alter facet selectivity during oriented attachment.

Connecting energy generation, electricity storage, and using sensors and control software to track load, including precommercial market marine energy generation technologies.

Summarizing the state of designed protein hybrid materials, researchers celebrate both the 50th anniversary of the MRS Bulletin and the 2025 Fred Kavli Distinguished Lecturers in Materials Science, Jim De Yoreo and David Baker.

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

Specially designed histidine-containing peptoids mimic carbonic anhydrase to accelerate calcite step growth.

Distributed science is thriving at PNNL, where scientists share data and collaborate with researchers around the world to increase the impact of the work.

Imaging ice microstructures formed by water freezing with atomic resolution for the first time.

Tailored assemblies mimic natural enzyme activity with significantly higher stability.

In high-entropy oxides, chromium tends to segregate during growth due to oxidation-induced migration of smaller, high-valence cations.

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

Researchers developed a way to precisely control dopant structures and locations in carbon-based materials.

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

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

High-resolution hydrodynamic-sediment modeling shows that inundation, suspended sediment concentration in the Amazon River, and floodplain hydrodynamics drive sediment deposition in Amazonian floodplains.

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

This study used historical data, remote sensing, and aquatic sensors to measure how far wildfire impacts propagated through the watershed after the 2022 Hermit’s Peak/Calf Canyon fire, New Mexico’s largest wildfire in history.

To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.