A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
Research that modeled increased heat pump adoption alongside climate change impacts in Texas showed that high-efficiency heat pumps buffer the strain that electric heating might put on the power grid.
The National Business Aviation Association has named Andre Watson, PNNL's director of Aviation Maintenance, to the 2024 class of the Business Aviation Top 40 Under 40.
The Sodium-ion Alliance for Grid Energy Storage, led by PNNL, is focused on demonstrating high-performance, low-cost, safe sodium-ion batteries tested for real-world grid applications.
This study evaluated the sensitivity of multiple geophysical methods to measure and evaluate the spatiotemporal variability of select soil properties across terrestrial–aquatic interfaces.
Research identifies the mechanisms through which peptoids affect ions in solution and a mineral surface, increasing the rate of carbonate crystal growth.
Researchers integrated field measurements, lab experiments, and model simulations to study oxygen consumption dynamics in soils along a coastal gradient.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
Pyrocumulonimbus clouds are increasing in frequency as large wildfires become more prevalent in a warming climate. These clouds can inject smoke particles into the atmosphere, where they can remain suspended for several months.
This research explores how changes in groundwater levels affect the chemistry of underground water, especially in areas where land meets water, like wetlands.
This study provides a comprehensive analysis of isolated deep convection & mesoscale convective systems using self-organizing maps to categorize large-scale meteorological patterns and a tracking algorithm to monitor their life cycle.