Summer internship programs with partnering colleges provide pathways for students to explore careers in science, technology, engineering, and math.

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.

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

A new review describes the insights that may be gained into important electrochemical processes using ion soft landing.

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

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

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.

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.

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

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.

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

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.

Chemist Grant Johnson offers tips for mentoring a successful internship and creating opportunities for undergraduate students to publish research.

Waste Management Symposia ‘Paper of Note’ and ‘Superior Paper’ awards recognize PNNL contributions to advancing radioactive waste and materials management.