Publisher will draw on Katrina Waters' expertise in public health and infectious disease.

New research sheds light on the biomolecular dangers of night shift work.

Vigorous exercise burns fat more in males than in females, but the benefits of exercise are broad for both sexes.

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.

PNNL electrical engineer Samrat Acharya led a team that earned the 2024 IEEE Innovative Smart Grid Technologies Conference Best Paper Award.

Data reveals mechanisms in our bodies that can help us fight viral pathogenesis.

New apps help researchers with statistical analyses of data.

The Health Physics Society has selected Jonathan Napier, a PNNL environmental health physicist, to serve as a delegate to the International Radiation Protection Association’s General Assembly.

Scientists have learned more about how to protect the insulin-producing cells that die in patients with Type 1 diabetes.

ChatGrid™ is a practical application of the Department of Energy’s exascale computing efforts and offers a new experience in easy, intuitive, and interactive data interaction.

Samantha Erwin, a PNNL data scientist, was recently appointed to the Society for Industrial and Applied Mathematics Membership Committee.

PNNL researchers helped identify a fragment from the SARS-CoV-2 virus that spurs severe illness.

Results of the PR100 study outline near- and short-term strategies for Puerto Rico to achieve a renewable power grid by 2050.

Pacific Northwest may face increase in summer heat-dome-like stationary waves.

Scientists have learned more about how drug resistance develops in patients with acute myeloid leukemia and how the process might be slowed.

Visual Sample Plan, a free software tool developed at PNNL that boosts statistics-based planning, has been recognized with a 2024 Federal Laboratory Consortium Award.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

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

PNNL scientists took thousands of measurements of firefighters in training to learn more about how the body responds to vigorous exercise.

A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.