Over the next four years, PNNL and University of Arizona will develop open-source computational tools to better identify and characterize the viruses associated with the human microbiome.
Armed with some of the world’s most advanced instrumentation, researchers at PNNL are working to analyze huge amounts of data and uncover hidden biological connections.
Led by interns from multiple DOE programs, a newly expanded dataset allows researchers to use easy-to-obtain measurements to determine the elemental composition of a promising carbon storage mineral.
PNNL’s year in review includes highlights ranging from advancing soil science to understanding Earth systems, expanding electricity transmission, detecting fentanyl, and applying artificial intelligence to aid scientific discovery.
This study evaluated the sensitivity of multiple geophysical methods to measure and evaluate the spatiotemporal variability of select soil properties across terrestrial–aquatic interfaces.
Researchers integrated field measurements, lab experiments, and model simulations to study oxygen consumption dynamics in soils along a coastal gradient.
This research explores how changes in groundwater levels affect the chemistry of underground water, especially in areas where land meets water, like wetlands.
Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.
