Bradley Crowell with the U.S. Nuclear Regulatory Commission sees advanced materials integrity, radiological measurement, and environmental capabilities on his first visit to PNNL.

Brown University Applied Mathematics and Engineering Professor George Karniadakis has driven solutions for science and engineering problems for over ten years with a joint appointment at PNNL.

Regional wind data helps utilities save money, plan for windy days.

PNNL energy storage experts express need for continued investment in developing and deploying long-duration energy storage.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

A holistic evaluation of the uncertainty sources that arise from configuring the model to processing the output for global variable-resolution models.

A success story of applying convergence testing to detect and address issues of numerical discretization in nonlinear representations of turbulence and clouds.

Researchers found a 150-day period in Antarctic circulation, something that many current climate models do not represent accurately.

The award was given at the 29th International Conference on Information, Communication and Automation Technologies.

Faced with limited data, researchers at PNNL studied different techniques to improve disease prediction in resource-limited settings.

Through collaboration with the Department of Homeland Security Soft Target Engineering to Neutralize the Threat Reality Center of Excellence, PNNL is advancing research and development of tools and methodologies to protect crowded places.

Two teams were recognized for technologies to help the International Atomic Energy Agency verify peaceful use of nuclear material.

Four PNNL researchers received highly competitive DOE Early Career Research Program awards, providing five continuous years of funding for their projects.

Zhijie (Jay) Xu will apply his expertise in multiscale modeling to this editorial role.

Scientists have developed a better way to recognize denial-of-service internet attacks, improving detection by 90 percent.

A new open-source feature tracking package is now available to facilitate advanced model evaluation, model development efforts, and scientific discovery.

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

PNNL recently joined the Department of Homeland Security for two technical meetings exploring national security research spanning the threat realm, from chemical and biological attacks to adversarial artificial intelligence.

ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility.

Joint appointments at PNNL and UTEP are teaming together to strengthen and protect sensitive data.