A decade after working as a post-bachelor’s researcher at PNNL, chemist Quin Miller is helping develop the workforce for the critical minerals-focused mines of the future.
A modeling study shows that adding batteries to a dam could decrease the wear and tear on hydropower turbines and open up new opportunities for dam operators to earn revenue.
From developing new energy storage materials to revealing patterns of Earth’s complex systems, studies led by PNNL researchers are recognized for their innovation and influence.
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.
The first direct molecular-scale evidence of the temperature-driven transformation of the coordination environment of ytterbium at geologically relevant conditions.
PNNL researchers continue to deliver high-quality, high-impact research on radioactive waste and nuclear materials management, earning “Papers of Note” and “Superior Paper” awards.
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.
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.
To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.
Engineers at PNNL devised a system that allows radar antennae to maintain stable orientation while mounted on platforms in open water that pitch and roll unpredictably. They were recently invited to participate in DOE's I-Corps program.
