A PNNL study developed a water management module for Xanthos that distinguishes between the operational characteristics of hydropower, irrigation, and flood control reservoirs.
Pacific Northwest National Laboratory launches the Training Outreach and Recruitment for Cybersecurity Hydropower program at the University of Texas at El Paso.
A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.
To identify communities ready for marine energy, help them realize their energy resilience goals, and facilitate community leadership in future projects, two national laboratories are developing the Deployment Readiness Framework.
Robert Rallo from Pacific Northwest National Laboratory will direct a machine learning thrust for a new Department of Energy-funded project led by SLAC National Accelerator Laboratory.
A team of researchers at PNNL has created a publicly available Hydropower eLibrary to improve access to information that could help streamline the FERC environmental review and licensing process.
PNNL led one of five Pathway Summer School programs nationwide, with a specific focus on engaging students from Native American or Indigenous backgrounds.
Researchers from Pacific Northwest National Laboratory created and embedded a physics-informed deep neural network that can learn as it processes data.
At the Nonproliferation, Counterproliferation, and Disarmament Science Gordon Research Conference, researchers from PNNL shared research and scientific approaches for countering diverse threats.
IDREAM research shows that keeping only the most important two- and three-body terms in reactive force fields can decrease computational cost by one order of magnitude, while preserving satisfactory accuracy.
