Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

CESER and PNNL convened a three-day summit with more than 100 state officials, cybersecurity experts, and industry leaders across 35 states to advance energy security planning, cyber risk assessment, and fortify protections against attacks.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

This project sought to assure that research activities centered around different sampling and monitoring efforts in northwest Ohio would not disturb any historical cultural resources.

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 multi-institutional team of researchers conducted a 13C-labeling greenhouse study using a semi-arid grassland soil, where they tracked the fate of 13C-labeled inputs from living roots and decaying roots from annual grass Avena barbata.

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.

In soil, microbes produce and consume methane. Using a technique called pool dilution, researchers can separate the rate of methane production and consumption from the net rate.

Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.

PNNL’s Climate Network with MSIs and HBCUs aims to bring opportunities to diverse populations.

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

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.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

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.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

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.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

The popular approach of organizing soil bacteria into fast- or slow-growing groups is problematic because most bacteria grow at comparable rates in soil.