By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.
Frederick Day-Lewis, Lab Fellow and chief geophysicist at PNNL, was named the 2024 recipient of the Geological Society of America Public Service Award.
Two renewable energy approaches—enhanced geothermal systems and floating offshore wind energy—get new focus as Energy Earthshot™ Research Centers at PNNL.
The diversity and function of organic matter in rivers at a large scale are influenced by factors, such as the types of vegetation covering the land, the energy characteristics, and the breakdown potential of the molecules.
Research shows that coupling geothermal power plants with lithium extraction from geothermal brine would make geothermal energy more economically viable, providing renewable energy and valuable raw materials.
Diefenderfer, Earth scientist who focuses on coastal ecosystems at PNNL, recently published “Ten Years of Gulf Coast Ecosystem Restoration Projects Since the Deepwater Horizon Oil Spill,” a cover article.
ICON science is a Department of Energy-developed framework to enhance scientific outcomes via more intentional design of research efforts across all domains of science.
This PNNL-developed separation system quickly and successfully separates larger particles from smaller ones at various scales, in different solid-liquid mixtures and at different flow rates.
An analysis of land use in watersheds that supply drinking water to over a hundred United States cities identified a wide range of exposure to potential contamination.
