An initiative from Washington State University and Snohomish County leaders is aiming to make Paine Field a nexus for testing and improving sustainable aviation fuels made from non-petroleum materials.
Scientists at PNNL have published a new article that focuses on understanding the composition, dynamics, and deployment of beneficial soil microbiomes to get the most out of soil.
Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere. Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere.
A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.
This study revealed that fresh organic vapors are soluble in particulate organics that are actively growing in size. However, if the particulate matter ages, fresh organic vapors can no longer mix with the organic matter.
Partitioning measured ice nucleating particle concentrations into individual particle types leads to a better understanding of the sources and model representations of these particles.
High fidelity simulations enabled by high-performance computing will allow for unprecedented predictive power of molecular level processes that are not amenable to experimental measurement.
A new discovery by PNNL researchers has illuminated a previously unknown key mechanism that could inform the development of new, more effective catalysts for abating NOx emissions from combustion-engines burning diesel or low carbon fuel.
Scientists can now generate a protein database directly from proteomics data gathered from a specific soil sample using a digital tool and deep learning computer model called Kaiko.
Corinne Fuller has been named the new co-director of the Bioproducts Institute, a research collaboration between Washington State University and PNNL, as of July 2023.
Researchers from Pacific Northwest National Laboratory created and embedded a physics-informed deep neural network that can learn as it processes data.
Randomly constructed neural networks can learn how to represent light interacting with atmospheric aerosols accurately at a low computational cost and improve climate modeling capabilities.
This study profiled the 24-hour rhythmicity in bile salt hydrolase enzyme activity using simple fluorescence assay and the results showed that this rhythmicity is influenced by feeding patterns of the host.