Localized gradients in magnetic fields have long-range effects on the concentration of rare earth ions in solution, facilitating field-driven extraction of critical minerals.
Hydrogen preferentially inserts at grain boundaries between interconnected chains of palladium nanoparticles, which have a lower energy barrier for hydrogen incorporation into the material.
Distributed science is thriving at PNNL, where scientists share data and collaborate with researchers around the world to increase the impact of the work.
Nanoscale domains of magnetically susceptible critical materials encounter enhanced magnetic interactions under external magnetic fields, providing a promising new avenue for separations.
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.
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.
High-resolution hydrodynamic-sediment modeling shows that inundation, suspended sediment concentration in the Amazon River, and floodplain hydrodynamics drive sediment deposition in Amazonian floodplains.
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.
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.