PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.
In the search for rare physics events, extremely pure materials are essential. A partnership between PNNL and Ultramet has led to tungsten with low contamination from other elements.
The Generator Scorecard, developed by PNNL in partnership with BPA, automates generator evaluations, reducing engineering workloads and improving grid reliability.
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.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
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.
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.”
PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.
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.
