PNNL researchers developed a new computational workflow to study day-to-night gene expression dynamics of cyanobacterium in real time.

ThermalTracker-3D can help streamline permitting, reduce costs, and shorten development time of energy projects.

Researchers at PNNL shared advances in artificial intelligence, cybersecurity, advanced imaging, and more at the Department of Homeland Security Research, Development, Test, and Evaluation Summit.

Understanding molecular modifications of proteins in the red yeast could help scientists re-engineer the organism’s phenotype.

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

Engineers at PNNL devised a system that allows radar antennae to maintain stable orientation while mounted on platforms in open water that pitch and roll unpredictably. They were recently invited to participate in DOE's I-Corps program.

Continued studies will deepen scientists’ understanding of virus-host interactions at the molecular level and also pave the way for developing better drugs to fight emerging viruses.

Flexible, high-throughput proteomics approach identifies protein modifications related to pancreatic stress and insulin production.

Scientists uncover how cyanobacteria's circadian cycle controls carbon and energy metabolism, increasing carbon dioxide-to-bioproducts yields.

Scientists map how transitions from day to night control gene regulatory networks in cyanobacteria, revealing key orchestrators of metabolic switching.

A team from PNNL contributed several articles to the Domestic Preparedness Journal showcasing recent efforts to explore the emergency management and artificial intelligence research and development landscape.

RemPlex and IAEA convene international leaders to tackle recruitment and retention in complex environmental cleanup efforts.

PNNL's accomplishments in FY 2024 help address the remaining challenges the wind industry faces.

PNNL scientists use proteomics to unveil how high-density lipoproteins protect against cholesterol accumulation in the artery wall.

Computing and artificial intelligence aid scientists who seek to understand function-driven design and control of biological systems.

With the launch of a large research barge, PNNL and collaborators took another significant step to improve offshore wind forecasting that will lower risk and cost associated with offshore wind energy development.

PNNL staff in the Artificial Intelligence and Data Analytics division were recognized by the TSA’s Innovation Task Force (ITF) for their contributions to cloud capabilities, development strategies, and smart management of cloud resources.

Researchers found that in a future where the Great Plains are 4 to 6 degrees Celsius (°C) warmer as projected in a high-emission scenario, these storms could bring three times more intense rainfall.