PNNL has developed a next-generation electrical resistivity tomography system for DOE that uses E4D software and AI-enhanced modeling to produce real-time subsurface images that help guide environmental remediation decisions.
This summer, PNNL hosted the inaugural “As Conductive As Copper” (AC2.0) workshop, fostering a collaborative conversation on the future of the U.S. copper supply chain.
Ampcera has an exclusive licensing agreement with PNNL to commercially develop and license a new battery material for applications such as vehicles and personal electronics.
Researchers developed a robust, cost-effective, and easy-to-use cap-based technique for spatial proteome mapping, addressing the lack of accessible proteomics technologies for studying tissue heterogeneity and microenvironments.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
Despite the widespread presence of RNA viruses in soils, little is known about the relative contributions and interactions of biological and environmental factors shaping the composition of soil RNA viral communities.
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.
A team of researchers from Pacific Northwest National Laboratory and the Environmental Molecular Sciences Laboratory developed a new and flexible software tool called “Advanced Spectra PCA Toolbox.”
Sequencing of microbiome and characterization of metabolome revealed significantly different functions of fine root systems from four temperate tree species in a 26-year-old common garden forest.
Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.
