Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.

PNNL study explored multiple factors that could impact future snowpack—a critical source of water for communities, irrigation and energy generation.

A streamlined informatics workflow that automatically processes complex data and provides the locations of double bonds in lipids.

Earth Scientist Laura Fierce mentors Department of Energy Science Graduate Student Research program awardees.

Hi-C metagenomics-informed phage-host infection networks detected in soil pre- and post-drying.

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.

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.

Metabolism metrics provide information about biological activity and carbon cycling in rivers. Conditions in large rivers differ from smaller rivers and require adjustments to existing methods.

Partitioning measured ice nucleating particle concentrations into individual particle types leads to a better understanding of the sources and model representations of these particles.

Scientists developed a process (or pipeline) that combined molecular probes—a specific chemical that binds to microbes carrying out a particular function—with a method that isolated these cells from their complex community.

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.

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.

Researchers from Pacific Northwest National Laboratory created and embedded a physics-informed deep neural network that can learn as it processes data.

Different sources of low-level moisture perturbation can result in differences in the timing and location of a large, modeled storm.

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.

Chun-Long Chen honored for his outstanding contributions in the field of bio-inspired nanomaterials.

PNNL welcomes six Department of Energy Office of Science Graduate Student Research awardees from across the nation.

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.

Across the United States, organic carbon concentration imposes a primary control on river sediment respiration, with additional influences from organic matter chemistry.

Small teams in the Biological Sciences Division at PNNL and at EMSL—the Environmental and Molecular Sciences Laboratory, an Office of Science user facility at PNNL—are pros at preparation.